a.scm

(define-module (guix-cran packages a)
  #:use-module (guix packages)
  #:use-module (guix download)
  #:use-module (guix build-system r)
  #:use-module ((guix licenses)
                #:prefix license:)
  #:use-module (gnu packages statistics)
  #:use-module (gnu packages cran)
  #:use-module (gnu packages pkg-config)
  #:use-module (gnu packages compression)
  #:use-module (gnu packages bioconductor)
  #:use-module (gnu packages gcc)
  #:use-module (gnu packages java)
  #:use-module (gnu packages multiprecision)
  #:use-module (gnu packages video)
  #:use-module (gnu packages backup)
  #:use-module (gnu packages geo)
  #:use-module (gnu packages python)
  #:use-module (guix-cran packages z)
  #:use-module (guix-cran packages y)
  #:use-module (guix-cran packages x)
  #:use-module (guix-cran packages w)
  #:use-module (guix-cran packages v)
  #:use-module (guix-cran packages u)
  #:use-module (guix-cran packages t)
  #:use-module (guix-cran packages s)
  #:use-module (guix-cran packages r)
  #:use-module (guix-cran packages q)
  #:use-module (guix-cran packages p)
  #:use-module (guix-cran packages o)
  #:use-module (guix-cran packages n)
  #:use-module (guix-cran packages m)
  #:use-module (guix-cran packages l)
  #:use-module (guix-cran packages k)
  #:use-module (guix-cran packages j)
  #:use-module (guix-cran packages i)
  #:use-module (guix-cran packages h)
  #:use-module (guix-cran packages g)
  #:use-module (guix-cran packages f)
  #:use-module (guix-cran packages e)
  #:use-module (guix-cran packages d)
  #:use-module (guix-cran packages c)
  #:use-module (guix-cran packages b))

(define-public r-azurevmmetadata
  (package
    (name "r-azurevmmetadata")
    (version "1.0.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AzureVMmetadata" version))
              (sha256
               (base32
                "15ghijzva6qzq2riq8ci4bh6ssknnp15yyy1fql0k4878wkf7vs0"))))
    (properties `((upstream-name . "AzureVMmetadata")))
    (build-system r-build-system)
    (propagated-inputs (list r-openssl r-httr))
    (home-page "https://cran.r-project.org/package=AzureVMmetadata")
    (synopsis "Interface to Azure Virtual Machine Instance Metadata")
    (description
     "This package provides a simple interface to the instance metadata for a virtual
machine running in Microsoft's Azure cloud.  This provides information about the
VM's configuration, such as its processors, memory, networking, storage, and so
on.  Part of the AzureR family of packages.")
    (license license:expat)))

(define-public r-azurevm
  (package
    (name "r-azurevm")
    (version "2.2.2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AzureVM" version))
              (sha256
               (base32
                "0766a4y17qgq3vgb398n6zn8sdjrv65gpvrnr9b9g89zdsdy9fc4"))))
    (properties `((upstream-name . "AzureVM")))
    (build-system r-build-system)
    (propagated-inputs (list r-r6 r-jsonlite r-azurermr))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=AzureVM")
    (synopsis "Virtual Machines in 'Azure'")
    (description
     "Functionality for working with virtual machines (VMs) in Microsoft's Azure
cloud: <https://azure.microsoft.com/en-us/services/virtual-machines/>.  Includes
facilities to deploy, startup, shutdown, and cleanly delete VMs and VM clusters.
 Deployment configurations can be highly customised, and can make use of
existing resources as well as creating new ones.  A selection of predefined
configurations is provided to allow easy deployment of commonly used Linux and
Windows images, including Data Science Virtual Machines.  With a running VM,
execute scripts and install optional extensions.  Part of the AzureR family of
packages.")
    (license license:expat)))

(define-public r-azurevision
  (package
    (name "r-azurevision")
    (version "1.0.2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AzureVision" version))
              (sha256
               (base32
                "0a4lnj60577bxy5vyd7yqji984kgwpwd4zykxz2d060r8l31rf42"))))
    (properties `((upstream-name . "AzureVision")))
    (build-system r-build-system)
    (propagated-inputs (list r-httr r-azurermr r-azurecognitive))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=AzureVision")
    (synopsis "Interface to Azure Computer Vision Services")
    (description
     "An interface to Azure Computer Vision
<https://docs.microsoft.com/azure/cognitive-services/Computer-vision/Home> and
Azure Custom Vision
<https://docs.microsoft.com/azure/cognitive-services/custom-vision-service/home>,
building on the low-level functionality provided by the AzureCognitive package.
These services allow users to leverage the cloud to carry out visual recognition
tasks using advanced image processing models, without needing powerful hardware
of their own.  Part of the AzureR family of packages.")
    (license license:expat)))

(define-public r-azuretablestor
  (package
    (name "r-azuretablestor")
    (version "1.0.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AzureTableStor" version))
              (sha256
               (base32
                "0xrfpi9psn1h21g4mvcbqsjav56s8cha381vsjkp1swilrxhmk5l"))))
    (properties `((upstream-name . "AzureTableStor")))
    (build-system r-build-system)
    (propagated-inputs (list r-vctrs
                             r-uuid
                             r-openssl
                             r-jsonlite
                             r-httr
                             r-azurestor
                             r-azurermr))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=AzureTableStor")
    (synopsis "Interface to the Table Storage Service in 'Azure'")
    (description
     "An interface to the table storage service in Azure':
<https://azure.microsoft.com/en-us/services/storage/tables/>.  Supplies
functionality for reading and writing data stored in tables, both as part of a
storage account and from a CosmosDB database with the table service API. Part of
the AzureR family of packages.")
    (license license:expat)))

(define-public r-azurestor
  (package
    (name "r-azurestor")
    (version "3.7.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AzureStor" version))
              (sha256
               (base32
                "0jrc4m8p0hss07hna157z510rh84lhjmyqsa47wirpr0b5ba6kr3"))))
    (properties `((upstream-name . "AzureStor")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml2
                             r-vctrs
                             r-r6
                             r-openssl
                             r-mime
                             r-httr
                             r-azurermr))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=AzureStor")
    (synopsis "Storage Management in 'Azure'")
    (description
     "Manage storage in Microsoft's Azure cloud:
<https://azure.microsoft.com/en-us/product-categories/storage/>.  On the admin
side, AzureStor includes features to create, modify and delete storage accounts.
 On the client side, it includes an interface to blob storage, file storage, and
Azure Data Lake Storage Gen2': upload and download files and blobs; list
containers and files/blobs; create containers; and so on.  Authenticated access
to storage is supported, via either a shared access key or a shared access
signature (SAS).  Part of the AzureR family of packages.")
    (license license:expat)))

(define-public r-azurermr
  (package
    (name "r-azurermr")
    (version "2.4.3")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AzureRMR" version))
              (sha256
               (base32
                "076hgxx2d6jf24fhysxk3mnp22ns8i6cqp3mzd64rafl1clqy3l1"))))
    (properties `((upstream-name . "AzureRMR")))
    (build-system r-build-system)
    (propagated-inputs (list r-uuid
                             r-r6
                             r-jsonlite
                             r-httr
                             r-azuregraph
                             r-azureauth))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=AzureRMR")
    (synopsis "Interface to 'Azure Resource Manager'")
    (description
     "This package provides a lightweight but powerful R interface to the Azure
Resource Manager REST API. The package exposes a comprehensive class framework
and related tools for creating, updating and deleting Azure resource groups,
resources and templates.  While AzureRMR can be used to manage any Azure
service, it can also be extended by other packages to provide extra
functionality for specific services.  Part of the AzureR family of packages.")
    (license license:expat)))

(define-public r-azureqstor
  (package
    (name "r-azureqstor")
    (version "1.0.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AzureQstor" version))
              (sha256
               (base32
                "1z7j8kakiarpw3q2rii7gl9zc2nsb49nzs1nxg1hgfyvcdhw2fcg"))))
    (properties `((upstream-name . "AzureQstor")))
    (build-system r-build-system)
    (propagated-inputs (list r-openssl r-httr r-azurestor r-azurermr))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=AzureQstor")
    (synopsis "Interface to 'Azure Queue Storage'")
    (description
     "An interface to Azure Queue Storage'.  This is a cloud service for storing large
numbers of messages, for example from automated sensors, that can be accessed
remotely via authenticated calls using HTTP or HTTPS. Queue storage is often
used to create a backlog of work to process asynchronously.  Part of the AzureR
family of packages.")
    (license license:expat)))

(define-public r-azuremlsdk
  (package
    (name "r-azuremlsdk")
    (version "1.10.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "azuremlsdk" version))
              (sha256
               (base32
                "0s64kjrmcdnjdwh5mdm5vxgvrl9ghvfv6bair7qfzz32jlab99m0"))))
    (properties `((upstream-name . "azuremlsdk")))
    (build-system r-build-system)
    (propagated-inputs (list r-shinycssloaders
                             r-shiny
                             r-servr
                             r-rstudioapi
                             r-reticulate
                             r-plyr
                             r-htmltools
                             r-ggplot2
                             r-dt))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/azure/azureml-sdk-for-r")
    (synopsis "Interface to the 'Azure Machine Learning' 'SDK'")
    (description
     "Interface to the Azure Machine Learning Software Development Kit ('SDK').  Data
scientists can use the SDK to train, deploy, automate, and manage machine
learning models on the Azure Machine Learning service.  To learn more about
Azure Machine Learning visit the website:
<https://docs.microsoft.com/en-us/azure/machine-learning/service/overview-what-is-azure-ml>.")
    (license license:expat)))

(define-public r-azurekusto
  (package
    (name "r-azurekusto")
    (version "1.0.7")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AzureKusto" version))
              (sha256
               (base32
                "16yxfc6pvb8bmv66h25bbjhwl7p42x6gxbzikjz9sy61lhlm76hw"))))
    (properties `((upstream-name . "AzureKusto")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyselect
                             r-tibble
                             r-rlang
                             r-r6
                             r-openssl
                             r-jsonlite
                             r-httr
                             r-dplyr
                             r-dbi
                             r-azurermr
                             r-azureauth))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=AzureKusto")
    (synopsis "Interface to 'Kusto'/'Azure Data Explorer'")
    (description
     "An interface to Azure Data Explorer', also known as Kusto', a fast, highly
scalable data exploration service from Microsoft:
<https://azure.microsoft.com/en-us/services/data-explorer/>.  Includes DBI and
dplyr interfaces, with the latter modelled after the dbplyr package, whereby
queries are translated from R into the native KQL query language and executed
lazily.  On the admin side, the package extends the object framework provided by
AzureRMR to support creation and deletion of databases, and management of
database principals.  Part of the AzureR family of packages.")
    (license license:expat)))

(define-public r-azurekeyvault
  (package
    (name "r-azurekeyvault")
    (version "1.0.5")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AzureKeyVault" version))
              (sha256
               (base32
                "15x0mkgn7pq2yk05l5vwvd744gxkz28nb5azc1yz502ayr1s6hnm"))))
    (properties `((upstream-name . "AzureKeyVault")))
    (build-system r-build-system)
    (propagated-inputs (list r-r6
                             r-openssl
                             r-jsonlite
                             r-jose
                             r-httr
                             r-azurermr
                             r-azuregraph
                             r-azureauth))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=AzureKeyVault")
    (synopsis "Key and Secret Management in 'Azure'")
    (description
     "Manage keys, certificates, secrets, and storage accounts in Microsoft's Key
Vault service: <https://azure.microsoft.com/services/key-vault/>.  Provides
facilities to store and retrieve secrets, use keys to encrypt, decrypt, sign and
verify data, and manage certificates.  Integrates with the AzureAuth package to
enable authentication with a certificate, and with the openssl package for
importing and exporting cryptographic objects.  Part of the AzureR family of
packages.")
    (license license:expat)))

(define-public r-azuregraph
  (package
    (name "r-azuregraph")
    (version "1.3.2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AzureGraph" version))
              (sha256
               (base32
                "19wppl05w98s711jgkxxia5dckc8k6xr5zzs52dcvnh67r4cbjq7"))))
    (properties `((upstream-name . "AzureGraph")))
    (build-system r-build-system)
    (propagated-inputs (list r-r6
                             r-openssl
                             r-jsonlite
                             r-httr
                             r-curl
                             r-azureauth))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=AzureGraph")
    (synopsis "Simple Interface to 'Microsoft Graph'")
    (description
     "This package provides a simple interface to the Microsoft Graph API
<https://docs.microsoft.com/en-us/graph/overview>.  Graph is a comprehensive
framework for accessing data in various online Microsoft services.  This package
was originally intended to provide an R interface only to the Azure Active
Directory part, with a view to supporting interoperability of R and Azure':
users, groups, registered apps and service principals.  However it has since
been expanded into a more general tool for interacting with Graph.  Part of the
AzureR family of packages.")
    (license license:expat)))

(define-public r-azurecosmosr
  (package
    (name "r-azurecosmosr")
    (version "1.0.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AzureCosmosR" version))
              (sha256
               (base32
                "07bpmjxfyzk1aq8r06biiqsn2ibv7ymgqccxfxkbvszpfq79nryj"))))
    (properties `((upstream-name . "AzureCosmosR")))
    (build-system r-build-system)
    (propagated-inputs (list r-vctrs
                             r-uuid
                             r-openssl
                             r-jsonlite
                             r-httr
                             r-curl
                             r-azurermr))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=AzureCosmosR")
    (synopsis "Interface to the 'Azure Cosmos DB' 'NoSQL' Database Service")
    (description
     "An interface to Azure CosmosDB':
<https://azure.microsoft.com/en-us/services/cosmos-db/>.  On the admin side,
AzureCosmosR provides functionality to create and manage Cosmos DB instances in
Microsoft's Azure cloud.  On the client side, it provides an interface to the
Cosmos DB SQL API, letting the user store and query documents and attachments in
Cosmos DB'.  Part of the AzureR family of packages.")
    (license license:expat)))

(define-public r-azurecontainers
  (package
    (name "r-azurecontainers")
    (version "1.3.2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AzureContainers" version))
              (sha256
               (base32
                "0lykvf4kk1q7b7ln4l8jlrxgqyvrg1cfnap4ak8zkhxmrgzqpc5f"))))
    (properties `((upstream-name . "AzureContainers")))
    (build-system r-build-system)
    (propagated-inputs (list r-r6
                             r-processx
                             r-openssl
                             r-httr
                             r-azurermr
                             r-azuregraph))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=AzureContainers")
    (synopsis
     "Interface to 'Container Instances', 'Docker Registry' and 'Kubernetes' in 'Azure'")
    (description
     "An interface to container functionality in Microsoft's Azure cloud:
<https://azure.microsoft.com/en-us/product-categories/containers/>.  Manage
Azure Container Instance (ACI), Azure Container Registry (ACR) and Azure
Kubernetes Service (AKS) resources, push and pull images, and deploy services.
On the client side, lightweight shells to the docker', docker-compose', kubectl
and helm commandline tools are provided.  Part of the AzureR family of packages.")
    (license license:expat)))

(define-public r-azurecognitive
  (package
    (name "r-azurecognitive")
    (version "1.0.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AzureCognitive" version))
              (sha256
               (base32
                "1mn3qw5g77x24qyhybhn1p3h4s9ymdafrj35i24f32ncr5abnd2f"))))
    (properties `((upstream-name . "AzureCognitive")))
    (build-system r-build-system)
    (propagated-inputs (list r-jsonlite r-httr r-azurermr r-azureauth))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=AzureCognitive")
    (synopsis "Interface to Azure Cognitive Services")
    (description
     "An interface to Azure Cognitive Services
<https://docs.microsoft.com/en-us/azure/cognitive-services/>.  Both an Azure
Resource Manager interface, for deploying Cognitive Services resources, and a
client framework are supplied.  While AzureCognitive can be called by the
end-user, it is meant to provide a foundation for other packages that will
support specific services, like Computer Vision, Custom Vision, language
translation, and so on.  Part of the AzureR family of packages.")
    (license license:expat)))

(define-public r-azureauth
  (package
    (name "r-azureauth")
    (version "1.3.3")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AzureAuth" version))
              (sha256
               (base32
                "1arr7vbcj9ibrx826md487hcmlch46b2h3r03a14wxq6ssxj4x0z"))))
    (properties `((upstream-name . "AzureAuth")))
    (build-system r-build-system)
    (propagated-inputs (list r-rappdirs
                             r-r6
                             r-openssl
                             r-jsonlite
                             r-jose
                             r-httr))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=AzureAuth")
    (synopsis "Authentication Services for Azure Active Directory")
    (description
     "This package provides Azure Active Directory (AAD) authentication functionality
for R users of Microsoft's Azure cloud <https://azure.microsoft.com/>.  Use this
package to obtain OAuth 2.0 tokens for services including Azure Resource
Manager, Azure Storage and others.  It supports both AAD v1.0 and v2.0, as well
as multiple authentication methods, including device code and resource owner
grant.  Tokens are cached in a user-specific directory obtained using the
rappdirs package.  The interface is based on the OAuth framework in the httr
package, but customised and streamlined for Azure.  Part of the AzureR family of
packages.")
    (license license:expat)))

(define-public r-azureappinsights
  (package
    (name "r-azureappinsights")
    (version "0.3.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AzureAppInsights" version))
              (sha256
               (base32
                "0dqk13r6iyaa54g21hda6fwijxlriq5dqnazvaw7cwh1zvivh8lm"))))
    (properties `((upstream-name . "AzureAppInsights")))
    (build-system r-build-system)
    (propagated-inputs (list r-shiny r-rlang r-lubridate r-jsonlite
                             r-assertthat))
    (home-page "https://cran.r-project.org/package=AzureAppInsights")
    (synopsis "Include Azure Application Insights in Shiny Apps")
    (description
     "Imports Azure Application Insights for web pages into Shiny apps via Microsoft's
JavaScript snippet.  Allows app developers to submit page tracking and submit
events.")
    (license license:expat)))

(define-public r-aziztest
  (package
    (name "r-aziztest")
    (version "0.2.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "aziztest" version))
              (sha256
               (base32
                "0rpnyrb7zi42l1fc8ni0r5d0y6a4dr56917z8i54mv1jrk4hijjd"))))
    (properties `((upstream-name . "aziztest")))
    (build-system r-build-system)
    (home-page "https://www.biorxiv.org/content/10.1101/2020.03.23.002972v2")
    (synopsis "Novel Statistical Test for Aberration Enrichment")
    (description
     "Testing for heterogeneous effects in a case-control setting.  The aim here to
discover an association that is beyond a mean difference between all cases and
all controls.  Instead, the signal of interest here is present in only a
proportion of the cases.  This test should be more powerful than a t-test or
Wilcoxon test in this heterogeneous setting.  Please cite the corresponding
paper: Mezlini et al. (2020) <doi:10.1101/2020.03.23.002972>.")
    (license license:gpl3)))

(define-public r-aziad
  (package
    (name "r-aziad")
    (version "0.0.2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AZIAD" version))
              (sha256
               (base32
                "0w5s367zkf857hzs1lczjgnd8ydnam8k5fwf155drxxdr5c3gm2z"))))
    (properties `((upstream-name . "AZIAD")))
    (build-system r-build-system)
    (propagated-inputs (list r-rootsolve
                             r-rmutil
                             r-qrm
                             r-mixall
                             r-matrixcalc
                             r-lqmm
                             r-foreach
                             r-extradistr
                             r-envstats
                             r-dplyr
                             r-doparallel
                             r-corpcor))
    (home-page "https://cran.r-project.org/package=AZIAD")
    (synopsis "Analyzing Zero-Inflated and Zero-Altered Data")
    (description
     "Computes maximum likelihood estimate of general, zero inflated, and zero altered
models for discrete and continuous distributions.  Computes Kolmogorov-Smirnov
(KS) test and likelihood ratio test for general, zero-inflated, and zero-altered
data.  It obtains the inverse of fisher information matrix and confidence
interval for the parameters of general, zero inflated, and zero altered models.
It simulate random deviates from zero inflated or hurdle models to obtain
maximum likelihood estimate.  It is based on the work of Aldirawi et al. (2022)
<doi:10.1007/s42519-021-00230-y>.")
    (license license:expat)))

(define-public r-aws-translate
  (package
    (name "r-aws-translate")
    (version "0.1.4")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "aws.translate" version))
              (sha256
               (base32
                "1x6cvpfddgwywsji4ywygmqn3pwy3i1aci9lk4nsrrfkzggwcbpb"))))
    (properties `((upstream-name . "aws.translate")))
    (build-system r-build-system)
    (propagated-inputs (list r-jsonlite r-httr r-aws-signature))
    (home-page "https://github.com/cloudyr/aws.translate")
    (synopsis "Client for 'AWS Translate'")
    (description
     "This package provides a client for AWS Translate
<https://aws.amazon.com/documentation/translate>, a machine translation service
that will convert a text input in one language into a text output in another
language.")
    (license license:gpl2+)))

(define-public r-aws-transcribe
  (package
    (name "r-aws-transcribe")
    (version "0.1.3")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "aws.transcribe" version))
              (sha256
               (base32
                "1nni1b935i2ir67lfhcj0106vzr310mk2jvln32gvzbnqxcggz7m"))))
    (properties `((upstream-name . "aws.transcribe")))
    (build-system r-build-system)
    (propagated-inputs (list r-jsonlite r-httr r-aws-signature))
    (home-page "https://github.com/cloudyr/aws.transcribe")
    (synopsis "Client for 'AWS Transcribe'")
    (description
     "Client for AWS Transcribe <https://aws.amazon.com/documentation/transcribe>, a
cloud transcription service that can convert an audio media file in English and
other languages into a text transcript.")
    (license license:gpl2+)))

(define-public r-aws-polly
  (package
    (name "r-aws-polly")
    (version "0.1.5")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "aws.polly" version))
              (sha256
               (base32
                "1xfx9g5iq1wcl27cmj4ss3y3f5yr1qmma77ki09g3ji2xvd50101"))))
    (properties `((upstream-name . "aws.polly")))
    (build-system r-build-system)
    (propagated-inputs (list r-tuner r-jsonlite r-httr r-aws-signature))
    (home-page "https://github.com/cloudyr/aws.polly")
    (synopsis "Client for AWS Polly")
    (description
     "This package provides a client for AWS Polly
<http://aws.amazon.com/documentation/polly>, a speech synthesis service.")
    (license license:gpl2+)))

(define-public r-aws-lambda
  (package
    (name "r-aws-lambda")
    (version "0.2.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "aws.lambda" version))
              (sha256
               (base32
                "0vp13qw7mw8dz01q30z7bnj47qx9js1zmxasc2n733gi07fdj62f"))))
    (properties `((upstream-name . "aws.lambda")))
    (build-system r-build-system)
    (propagated-inputs (list r-jsonlite r-httr r-base64enc r-aws-signature))
    (home-page "https://github.com/cloudyr/aws.lambda")
    (synopsis "AWS Lambda Client Package")
    (description
     "This package provides a simple client package for the Amazon Web Services
('AWS') Lambda API <https://aws.amazon.com/lambda/>.")
    (license license:gpl3)))

(define-public r-aws-kms
  (package
    (name "r-aws-kms")
    (version "0.1.4")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "aws.kms" version))
              (sha256
               (base32
                "0f9l62g4z68ickzi4if3pw3algb41rn47z9cpxga8aggkclk86l4"))))
    (properties `((upstream-name . "aws.kms")))
    (build-system r-build-system)
    (propagated-inputs (list r-jsonlite r-httr r-base64enc r-aws-signature))
    (home-page "https://github.com/cloudyr/aws.kms")
    (synopsis "'AWS Key Management Service' Client Package")
    (description
     "Client package for the AWS Key Management Service <https://aws.amazon.com/kms/>,
a cloud service for managing encryption keys.")
    (license license:gpl2+)))

(define-public r-aws-iam
  (package
    (name "r-aws-iam")
    (version "0.1.8")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "aws.iam" version))
              (sha256
               (base32
                "1p4w50icfw6mrzr6aazdbh977yvyvsf1yavjscyvv11xf3y9f9j2"))))
    (properties `((upstream-name . "aws.iam")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml2 r-jsonlite r-httr r-aws-signature))
    (home-page "https://github.com/cloudyr/aws.iam")
    (synopsis "AWS IAM Client Package")
    (description
     "This package provides a simple client for the Amazon Web Services ('AWS')
Identity and Access Management ('IAM') API <https://aws.amazon.com/iam/>.")
    (license license:gpl2+)))

(define-public r-aws-ecx
  (package
    (name "r-aws-ecx")
    (version "1.0.5")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "aws.ecx" version))
              (sha256
               (base32
                "1yz20h2k5rf13jsgpk8aj6d27a1zj602g916pngq525m08cmbvka"))))
    (properties `((upstream-name . "aws.ecx")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml2 r-rjson r-httr r-aws-signature))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/Jiefei-Wang/aws.ecx")
    (synopsis "Communicating with AWS EC2 and ECS using AWS REST APIs")
    (description
     "Providing the functions for communicating with Amazon Web Services(AWS) Elastic
Compute Cloud(EC2) and Elastic Container Service(ECS).  The functions will have
the prefix ecs_ or ec2_ depending on the class of the API. The request will be
sent via the REST API and the parameters are given by the function argument.
The credentials can be set via aws_set_credentials'.  The EC2 documentation can
be found at
<https://docs.aws.amazon.com/AWSEC2/latest/APIReference/Welcome.html> and ECS
can be found at
<https://docs.aws.amazon.com/AmazonECS/latest/APIReference/Welcome.html>.")
    (license license:gpl3)))

(define-public r-aws-ec2metadata
  (package
    (name "r-aws-ec2metadata")
    (version "0.2.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "aws.ec2metadata" version))
              (sha256
               (base32
                "1lbljg2fp3yh1hwlbmprkc1prw80jv0ycvpg1vggagm68wm5x288"))))
    (properties `((upstream-name . "aws.ec2metadata")))
    (build-system r-build-system)
    (propagated-inputs (list r-jsonlite r-curl))
    (home-page "https://github.com/cloudyr/aws.ec2metadata")
    (synopsis "Get EC2 Instance Metadata")
    (description
     "Retrieve Amazon EC2 instance metadata from within the running instance.")
    (license license:gpl2+)))

(define-public r-aws-comprehend
  (package
    (name "r-aws-comprehend")
    (version "0.2.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "aws.comprehend" version))
              (sha256
               (base32
                "0qn4mkdd17c8kmrm4ml7l1x3rzaw3gbykhrj3m0ga53crcqdhqri"))))
    (properties `((upstream-name . "aws.comprehend")))
    (build-system r-build-system)
    (propagated-inputs (list r-jsonlite r-httr r-aws-signature))
    (home-page "https://github.com/cloudyr/aws.comprehend")
    (synopsis "Client for 'AWS Comprehend'")
    (description
     "Client for AWS Comprehend <https://aws.amazon.com/comprehend>, a cloud natural
language processing service that can perform a number of quantitative text
analyses, including language detection, sentiment analysis, and feature
extraction.")
    (license license:gpl2+)))

(define-public r-aws-alexa
  (package
    (name "r-aws-alexa")
    (version "0.1.8")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "aws.alexa" version))
              (sha256
               (base32
                "0m1i1xgi9fqixq90ai2ag0079aa75nlyhbr3ln3yhk5g8zx9i9m9"))))
    (properties `((upstream-name . "aws.alexa")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml2 r-httr r-dplyr r-aws-signature))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=aws.alexa")
    (synopsis "Client for the Amazon Alexa Web Information Services API")
    (description
     "Use the Amazon Alexa Web Information Services API to find information about
domains, including the kind of content that they carry, how popular are
they---rank and traffic history, sites linking to them, among other things.  See
<https://aws.amazon.com/awis/> for more information.")
    (license license:expat)))

(define-public r-awr-kms
  (package
    (name "r-awr-kms")
    (version "0.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AWR.KMS" version))
              (sha256
               (base32
                "00aqhyqlncsv0vfcyhaazxaclwm63v5kscssash7529avdwd4gqg"))))
    (properties `((upstream-name . "AWR.KMS")))
    (build-system r-build-system)
    (propagated-inputs (list r-rjava r-jsonlite r-awr))
    (home-page "https://github.com/cardcorp/AWR.KMS")
    (synopsis "Simple Client to the 'AWS' Key Management Service")
    (description
     "Encrypt plain text and decrypt cipher text using encryption keys hosted at
Amazon Web Services ('AWS') Key Management Service ('KMS'), on which see
<https://aws.amazon.com/kms> for more information.")
    (license license:agpl3)))

(define-public r-awr-kinesis
  (package
    (name "r-awr-kinesis")
    (version "1.7.3")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AWR.Kinesis" version))
              (sha256
               (base32
                "1gfjzbb8xxfd2x5zabysqi0x10sb1c9826wqw8y555nsxgksqxz8"))))
    (properties `((upstream-name . "AWR.Kinesis")))
    (build-system r-build-system)
    (propagated-inputs (list r-rjava r-jsonlite r-futile-logger r-awr))
    (home-page "https://github.com/cardcorp/AWR.Kinesis")
    (synopsis "Amazon 'Kinesis' Consumer Application for Stream Processing")
    (description
     "Fetching data from Amazon Kinesis Streams using the Java-based MultiLangDaemon
interacting with Amazon Web Services ('AWS') for easy stream processing from R.
For more information on Kinesis', see <https://aws.amazon.com/kinesis>.")
    (license license:agpl3)))

(define-public r-awr-athena
  (package
    (name "r-awr-athena")
    (version "2.0.7-0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AWR.Athena" version))
              (sha256
               (base32
                "1j9bqhyk0jzry4g379ml65gwxlszn7pjif1dywgns98jbry8mavh"))))
    (properties `((upstream-name . "AWR.Athena")))
    (build-system r-build-system)
    (propagated-inputs (list r-rjdbc r-rjava))
    (home-page "https://cran.r-project.org/package=AWR.Athena")
    (synopsis "'AWS' Athena 'DBI' Wrapper")
    (description
     "RJDBC based DBI driver to Amazon Athena, which is an interactive query service
to analyze data in Amazon S3 using standard SQL'.")
    (license license:agpl3)))

(define-public r-awr
  (package
    (name "r-awr")
    (version "1.11.189-1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AWR" version))
              (sha256
               (base32
                "1imvpmq6br0z7l67w66a5s1ylbv6xvypj0wc09bmjy7sapdmkn4x"))))
    (properties `((upstream-name . "AWR")))
    (build-system r-build-system)
    (propagated-inputs (list r-rjava))
    (home-page "https://github.com/daroczig/AWR")
    (synopsis "'AWS' Java 'SDK' for R")
    (description
     "Make the compiled Java modules of the Amazon Web Services ('AWS') SDK available
to be used in downstream R packages interacting with AWS'.  See
<https://aws.amazon.com/sdk-for-java> for more information on the AWS SDK for
Java.")
    (license license:agpl3)))

(define-public r-awinr
  (package
    (name "r-awinr")
    (version "0.1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "awinR" version))
              (sha256
               (base32
                "09cp9wfb4aslfddlk72n0kawfghyn1fcjya5afjhiffwww5ps3iy"))))
    (properties `((upstream-name . "awinR")))
    (build-system r-build-system)
    (propagated-inputs (list r-jsonlite))
    (native-inputs (list r-knitr))
    (home-page "https://windsor.ai/")
    (synopsis "Get Data from 'Awin' via the 'Windsor.ai' API")
    (description
     "Collect your data on digital marketing campaigns from Awin using the Windsor.ai
API <https://windsor.ai/api-fields/>.")
    (license license:gpl3)))

(define-public r-awesom
  (package
    (name "r-awesom")
    (version "1.3")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "aweSOM" version))
              (sha256
               (base32
                "0nfbn7rgazvc5nljf8i7bwpxy5j0w404bnrvi02k97jvmrra1dyb"))))
    (properties `((upstream-name . "aweSOM")))
    (build-system r-build-system)
    (propagated-inputs (list r-viridis
                             r-shiny
                             r-rmarkdown
                             r-readxl
                             r-readods
                             r-rcolorbrewer
                             r-rclipboard
                             r-kohonen
                             r-kernlab
                             r-htmlwidgets
                             r-htmltools
                             r-haven
                             r-ggplot2
                             r-foreign
                             r-fields
                             r-e1071
                             r-dt
                             r-data-table
                             r-cluster
                             r-bslib))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=aweSOM")
    (synopsis "Interactive Self-Organizing Maps")
    (description
     "Self-organizing maps (also known as SOM, see Kohonen (2001)
<doi:10.1007/978-3-642-56927-2>) are a method for dimensionality reduction and
clustering of continuous data.  This package introduces interactive (html)
graphics for easier analysis of SOM results.  It also features an interactive
interface, for push-button training and visualization of SOM on numeric,
categorical or mixed data, as well as tools to evaluate the quality of SOM.")
    (license license:gpl2+)))

(define-public r-aweek
  (package
    (name "r-aweek")
    (version "1.0.3")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "aweek" version))
              (sha256
               (base32
                "14n1xmargr89mf4n0bdzdwn7qh314a1xg1bid5px762vk0qf4fws"))))
    (properties `((upstream-name . "aweek")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://www.repidemicsconsortium.org/aweek/")
    (synopsis "Convert Dates to Arbitrary Week Definitions")
    (description
     "Which day a week starts depends heavily on the either the local or professional
context.  This package is designed to be a lightweight solution to easily
switching between week-based date definitions.")
    (license license:expat)))

(define-public r-avocado
  (package
    (name "r-avocado")
    (version "0.1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "avocado" version))
              (sha256
               (base32
                "0qy9ripwydm3f70rpxwk0asc7r25hg8jcbrr4rz8bxs93q1lsz8x"))))
    (properties `((upstream-name . "avocado")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=avocado")
    (synopsis "Weekly Hass Avocado Sales Summary")
    (description
     "This package provides a weekly summary of Hass Avocado sales for the contiguous
US from January 2017 to November 2020.  See the package website for more
information, documentation, and examples.  Data source: Haas Avocado Board
<https://hassavocadoboard.com/category-data/>.")
    (license license:expat)))

(define-public r-avirtualtwins
  (package
    (name "r-avirtualtwins")
    (version "1.0.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "aVirtualTwins" version))
              (sha256
               (base32
                "1jg19ns3mxfycc11i2c152d83n4kqz3dd6d269sijnxrw80kzjki"))))
    (properties `((upstream-name . "aVirtualTwins")))
    (build-system r-build-system)
    (propagated-inputs (list r-rpart r-randomforest r-party))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/prise6/aVirtualTwins")
    (synopsis "Adaptation of Virtual Twins Method from Jared Foster")
    (description
     "Research of subgroups in random clinical trials with binary outcome and two
treatments groups.  This is an adaptation of the Jared Foster method
(<https://www.ncbi.nlm.nih.gov/pubmed/21815180>).")
    (license (list license:gpl3
                   (license:fsdg-compatible "file://LICENSE")))))

(define-public r-avinertia
  (package
    (name "r-avinertia")
    (version "0.0.2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AvInertia" version))
              (sha256
               (base32
                "1i3fy4jf91x662xhi07kcsg9b1p0hfyj2x5fav3zkvs9lx7gwfqx"))))
    (properties `((upstream-name . "AvInertia")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-stringr
                             r-reshape2
                             r-readxl
                             r-pracma
                             r-ggthemes
                             r-ggplot2))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/charvey23/AvInertia")
    (synopsis "Calculate the Inertial Properties of a Flying Bird")
    (description
     "Tools to compute the center of gravity and moment of inertia tensor of any
flying bird.  The tools function by modeling a bird as a composite structure of
simple geometric objects.  This requires detailed morphological measurements of
bird specimens although those obtained for the associated paper have been
included in the package for use.  Refer to the vignettes and supplementary
material for detailed information on the package function.")
    (license license:gpl3)))

(define-public r-avidar
  (package
    (name "r-avidar")
    (version "1.1.3")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "avidaR" version))
              (sha256
               (base32
                "1ahva473dhhbwlxlm9qz2x0ssmqg1hw1imnab39dijvmspaqvk5v"))))
    (properties `((upstream-name . "avidaR")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml2
                             r-tidyr
                             r-tibble
                             r-readr
                             r-rcolorbrewer
                             r-r6
                             r-httr
                             r-dplyr
                             r-circlize
                             r-base64enc))
    (home-page "https://gitlab.com/fortunalab/avidaR")
    (synopsis "Computational Biologist’s Toolkit To Get Data From 'avidaDB'")
    (description
     "Easy-to-use tools for performing complex queries on avidaDB', a semantic
database that stores genomic and transcriptomic data of self-replicating
computer programs (known as digital organisms) that mutate and evolve within a
user-defined computational environment.")
    (license license:expat)))

(define-public r-avfintools
  (package
    (name "r-avfintools")
    (version "0.1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "avfintools" version))
              (sha256
               (base32
                "1v04z9qr80zikjb5q0h9796sgnmw43l5ygxs99gsgsghlyj9nrla"))))
    (properties `((upstream-name . "avfintools")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble
                             r-plotly
                             r-lubridate
                             r-ggplot2
                             r-dplyr
                             r-alphavantager))
    (home-page "https://cran.r-project.org/package=avfintools")
    (synopsis "Financial Analysis Tools Using Data from 'Alpha Vantager'")
    (description
     "To pull data from ALPHA VANTAGE <https://www.alphavantage.co/>, use the
av_api_key() function from alphavantager for inserting your API key.  This is a
complement to the alphavantager package from CRAN. Contains commonly used
quantitative finance tools.  avfintools stands for ALPHA VANTAGE Finance Tools,
as it depends on sourcing financial data from the ALPHA VANTAGE
<https://www.alphavantage.co/documentation/> API.")
    (license license:cc0)))

(define-public r-averisk
  (package
    (name "r-averisk")
    (version "1.0.3")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "averisk" version))
              (sha256
               (base32
                "02j27d4jxgy2bk5sgxp1xdfyqr321civs99qj0g8cp34gwqk0j3m"))))
    (properties `((upstream-name . "averisk")))
    (build-system r-build-system)
    (propagated-inputs (list r-mass))
    (home-page "https://cran.r-project.org/package=averisk")
    (synopsis
     "Calculation of Average Population Attributable Fractions and Confidence Intervals")
    (description
     "Average population attributable fractions are calculated for a set of risk
factors (either binary or ordinal valued) for both prospective and case- control
designs.  Confidence intervals are found by Monte Carlo simulation.  The method
can be applied to either prospective or case control designs, provided an
estimate of disease prevalence is provided.  In addition to an exact calculation
of AF, an approximate calculation, based on randomly sampling permutations has
been implemented to ensure the calculation is computationally tractable when the
number of risk factors is large.")
    (license license:cc0)))

(define-public r-avar
  (package
    (name "r-avar")
    (version "0.1.2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "avar" version))
              (sha256
               (base32
                "14wiqg4f6paac6n5cwmdpy6z03w3fll6js4yhr80zhj1k2qdh1fa"))))
    (properties `((upstream-name . "avar")))
    (build-system r-build-system)
    (propagated-inputs (list r-simts r-rcpparmadillo r-rcpp))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/SMAC-Group/avar")
    (synopsis "Allan Variance")
    (description
     "This package implements the allan variance and allan variance linear regression
estimator for latent time series models.  More details about the method can be
found, for example, in Guerrier, S., Molinari, R., & Stebler, Y. (2016)
<doi:10.1109/LSP.2016.2541867>.")
    (license license:agpl3)))

(define-public r-available
  (package
    (name "r-available")
    (version "1.1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "available" version))
              (sha256
               (base32
                "1j6z0zwd7xjk6j6wk74fjq3nhx9gk7ys09i543gakcskmdm59dw4"))))
    (properties `((upstream-name . "available")))
    (build-system r-build-system)
    (propagated-inputs (list r-yesno
                             r-tidytext
                             r-tibble
                             r-stringdist
                             r-snowballc
                             r-memoise
                             r-jsonlite
                             r-glue
                             r-desc
                             r-crayon
                             r-clisymbols
                             r-cli))
    (home-page "https://github.com/r-lib/available")
    (synopsis
     "Check if the Title of a Package is Available, Appropriate and Interesting")
    (description
     "Check if a given package name is available to use.  It checks the name's
validity.  Checks if it is used on GitHub', CRAN and Bioconductor'.  Checks for
unintended meanings by querying Wiktionary and Wikipedia.")
    (license license:expat)))

(define-public r-av
  (package
    (name "r-av")
    (version "0.8.2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "av" version))
              (sha256
               (base32
                "08h99iy05s1r9ix1i0mbzpz14hhvk0ima9165hhlxkl7w6qqld9j"))))
    (properties `((upstream-name . "av")))
    (build-system r-build-system)
    (inputs (list zlib))
    (native-inputs (list pkg-config))
    (home-page "https://docs.ropensci.org/av/")
    (synopsis "Working with Audio and Video in R")
    (description
     "Bindings to FFmpeg <http://www.ffmpeg.org/> AV library for working with audio
and video in R. Generates high quality video from images or R graphics with
custom audio.  Also offers high performance tools for reading raw audio,
creating spectrograms', and converting between countless audio / video formats.
This package interfaces directly to the C API and does not require any command
line utilities.")
    (license license:expat)))

(define-public r-autoweatherindices
  (package
    (name "r-autoweatherindices")
    (version "0.1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AutoWeatherIndices" version))
              (sha256
               (base32
                "08f2c026vn5kmsdlf54sxakzjp2f43dkrs6mv9qwnjfrd2hchzzi"))))
    (properties `((upstream-name . "AutoWeatherIndices")))
    (build-system r-build-system)
    (propagated-inputs (list r-hmisc r-gtools))
    (home-page "https://cran.r-project.org/package=AutoWeatherIndices")
    (synopsis "Calculating Weather Indices")
    (description
     "Weather indices are formed from weather variables in this package.  The users
can input any number of weather variables recorded over any number of weeks.
This package has no restriction on the number of weeks and weather variables to
be taken as input.The details of the method can be seen (i)'Joint effects of
weather variables on rice yields by R. Agrawal, R. C. Jain and M. P. Jha in
Mausam, vol.  34, pp.  189-194,
1983,<doi:10.54302/mausam.v34i2.2392>,(ii)'Improved weather indices based
Bayesian regression model for forecasting crop yield by M. Yeasin, K. N. Singh,
A. Lama and B. Gurung in Mausam, vol.  72, pp.879-886,
2021,<doi:10.54302/mausam.v72i4.670>.")
    (license license:gpl3)))

(define-public r-autots
  (package
    (name "r-autots")
    (version "0.9.11")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "autoTS" version))
              (sha256
               (base32
                "1mwpazynp5hdc2ccnhvddkajfcd4qam23pvjl9accq1rnxzxkiyv"))))
    (properties `((upstream-name . "autoTS")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-shinycssloaders
                             r-shiny
                             r-rlang
                             r-rcpproll
                             r-prophet
                             r-plotly
                             r-magrittr
                             r-lubridate
                             r-ggplot2
                             r-forecast
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/vivienroussez/autoTS")
    (synopsis
     "Automatic Model Selection and Prediction for Univariate Time Series")
    (description
     "Offers a set of functions to easily make predictions for univariate time series.
 autoTS is a wrapper of existing functions of the forecast and prophet packages,
harmonising their outputs in tidy dataframes and using default values for each.
The core function getBestModel() allows the user to effortlessly benchmark seven
algorithms along with a bagged estimator to identify which one performs the best
for a given time series.")
    (license license:gpl3)))

(define-public r-autothresholdr
  (package
    (name "r-autothresholdr")
    (version "1.4.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "autothresholdr" version))
              (sha256
               (base32
                "1n8kfl7zk7smwmkj1rlp4j4i0jnwi2f0aw58jhlf7ivahrq0rmnk"))))
    (properties `((upstream-name . "autothresholdr")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr
                             r-strex
                             r-rlang
                             r-rcpp
                             r-purrr
                             r-magrittr
                             r-ijtiff
                             r-checkmate))
    (native-inputs (list r-knitr))
    (home-page "https://rorynolan.github.io/autothresholdr/")
    (synopsis "An R Port of the 'ImageJ' Plugin 'Auto Threshold'")
    (description
     "Algorithms for automatically finding appropriate thresholds for numerical data,
with special functions for thresholding images.  Provides the ImageJ Auto
Threshold plugin functionality to R users.  See
<https://imagej.net/plugins/auto-threshold> and Landini et al. (2017)
<DOI:10.1111/jmi.12474>.")
    (license license:gpl3)))

(define-public r-autostsm
  (package
    (name "r-autostsm")
    (version "3.0.3")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "autostsm" version))
              (sha256
               (base32
                "1d80l7lxzrpwdd92cc41ykj2ylkdhndamqphprw9a3wf0zn7l39d"))))
    (properties `((upstream-name . "autostsm")))
    (build-system r-build-system)
    (propagated-inputs (list r-strucchange
                             r-sandwich
                             r-progress
                             r-maxlik
                             r-lubridate
                             r-lmtest
                             r-kalmanfilter
                             r-gridextra
                             r-ggrepel
                             r-ggplot2
                             r-forecast
                             r-foreach
                             r-dosnow
                             r-data-table))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=autostsm")
    (synopsis "Automatic Structural Time Series Models")
    (description
     "Automatic model selection for structural time series decomposition into trend,
cycle, and seasonal components, plus optionality for structural interpolation,
using the Kalman filter.  Koopman, Siem Jan and Marius Ooms (2012) \"Forecasting
Economic Time Series Using Unobserved Components Time Series Models\"
<doi:10.1093/oxfordhb/9780195398649.013.0006>.  Kim, Chang-Jin and Charles R.
Nelson (1999) \"State-Space Models with Regime Switching: Classical and
Gibbs-Sampling Approaches with Applications\"
<doi:10.7551/mitpress/6444.001.0001><http://econ.korea.ac.kr/~cjkim/>.")
    (license license:gpl2+)))

(define-public r-autostepwiseglm
  (package
    (name "r-autostepwiseglm")
    (version "0.2.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AutoStepwiseGLM" version))
              (sha256
               (base32
                "0wwi8hg2q1zkf28rq7bj0f9fcxc5hj59hkmk0gl9p8i3rghlyrms"))))
    (properties `((upstream-name . "AutoStepwiseGLM")))
    (build-system r-build-system)
    (propagated-inputs (list r-formula-tools r-caret))
    (home-page "https://cran.r-project.org/package=AutoStepwiseGLM")
    (synopsis "Builds Stepwise GLMs via Train and Test Approach")
    (description
     "Randomly splits data into testing and training sets.  Then, uses stepwise
selection to fit numerous multiple regression models on the training data, and
tests them on the test data.  Returned for each model are plots comparing model
Akaike Information Criterion (AIC), Pearson correlation coefficient (r) between
the predicted and actual values, Mean Absolute Error (MAE), and R-Squared among
the models.  Each model is ranked relative to the other models by the model
evaluation metrics (i.e., AIC, r, MAE, and R-Squared) and the model with the
best mean ranking among the model evaluation metrics is returned.  Model
evaluation metric weights for AIC, r, MAE, and R-Squared are taken in as
arguments as aic_wt, r_wt, mae_wt, and r_squ_wt, respectively.  They are equally
weighted as default but may be adjusted relative to each other if the user
prefers one or more metrics to the others, Field, A. (2013,
ISBN:978-1-4462-4918-5).")
    (license license:expat)))

(define-public r-autostats
  (package
    (name "r-autostats")
    (version "0.4.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "autostats" version))
              (sha256
               (base32
                "0xyfv2akv308g3r0wq2dcg7l24p6bf3524x1ikj1lfmw07hca6k6"))))
    (properties `((upstream-name . "autostats")))
    (build-system r-build-system)
    (propagated-inputs (list r-yardstick
                             r-xgboost
                             r-workflows
                             r-tune
                             r-tidyselect
                             r-tidyr
                             r-tibble
                             r-stringr
                             r-rsample
                             r-rlist
                             r-rlang
                             r-recosystem
                             r-recipes
                             r-purrr
                             r-presenter
                             r-patchwork
                             r-party
                             r-parsnip
                             r-nnet
                             r-magrittr
                             r-jtools
                             r-janitor
                             r-gtools
                             r-ggthemes
                             r-ggplot2
                             r-ggeasy
                             r-framecleaner
                             r-dplyr
                             r-dials
                             r-data-table
                             r-broom))
    (native-inputs (list r-knitr))
    (home-page "https://harrison4192.github.io/autostats/")
    (synopsis "Auto Stats")
    (description
     "Automatically do statistical exploration.  Create formulas using tidyselect
syntax, and then determine cross-validated model accuracy and variable
contributions using glm and xgboost'.  Contains additional helper functions to
create and modify formulas.  Has a flagship function to quickly determine
relationships between categorical and continuous variables in the data set.")
    (license license:expat)))

(define-public r-autoshiny
  (package
    (name "r-autoshiny")
    (version "0.0.2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "autoshiny" version))
              (sha256
               (base32
                "0s06ynnirgsh19x8qq4020piirkhvjqpvz372syygvlal062y6cn"))))
    (properties `((upstream-name . "autoshiny")))
    (build-system r-build-system)
    (propagated-inputs (list r-shiny))
    (home-page "https://github.com/alekrutkowski/autoshiny")
    (synopsis "Automatic Transformation of an 'R' Function into a 'shiny' App")
    (description
     "Static code compilation of a shiny app given an R function (into ui.R and
server.R files or into a shiny app object).  See examples at
<https://github.com/alekrutkowski/autoshiny>.")
    (license license:gpl2)))

(define-public r-autoseed
  (package
    (name "r-autoseed")
    (version "0.1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "Autoseed" version))
              (sha256
               (base32
                "0xr3sjfccvp8h18jqxzajb2pfn4nm8q9maic6k9zzr15fxvphiy5"))))
    (properties `((upstream-name . "Autoseed")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=Autoseed")
    (synopsis "Retrieve Disease-Related Genes from Public Sources")
    (description
     "For researchers to quickly and comprehensively acquire disease genes, so as to
understand the mechanism of disease, we developed this program to acquire
disease-related genes.  The data is integrated from three public databases.  The
three databases are eDGAR', DrugBank and MalaCards'.  The eDGAR is a
comprehensive database, containing data on the relationship between disease and
genes.  DrugBank contains information on 13443 drugs and 5157 targets.
MalaCards integrates human disease information, including disease-related genes.")
    (license license:gpl3+)))

(define-public r-autoscore
  (package
    (name "r-autoscore")
    (version "1.0.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AutoScore" version))
              (sha256
               (base32
                "14wn566xm308zir12rckwc5fagm2x1mrphy0a7iri0cbrffgnkz4"))))
    (properties `((upstream-name . "AutoScore")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-tableone
                             r-survminer
                             r-survival
                             r-survauc
                             r-rlang
                             r-randomforestsrc
                             r-randomforest
                             r-proc
                             r-plotly
                             r-ordinal
                             r-magrittr
                             r-knitr
                             r-hmisc
                             r-ggplot2
                             r-dplyr
                             r-coxed
                             r-car))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/nliulab/AutoScore")
    (synopsis
     "An Interpretable Machine Learning-Based Automatic Clinical Score Generator")
    (description
     "This package provides a novel interpretable machine learning-based framework to
automate the development of a clinical scoring model for predefined outcomes.
Our novel framework consists of six modules: variable ranking with machine
learning, variable transformation, score derivation, model selection, domain
knowledge-based score fine-tuning, and performance evaluation.The The original
AutoScore structure is described in the research paper<doi:10.2196/21798>.  A
full tutorial can be found here<https://nliulab.github.io/AutoScore/>.  Users or
clinicians could seamlessly generate parsimonious sparse-score risk models
(i.e., risk scores), which can be easily implemented and validated in clinical
practice.  We hope to see its application in various medical case studies.")
    (license license:gpl2+)))

(define-public r-autoregressionmde
  (package
    (name "r-autoregressionmde")
    (version "1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AutoregressionMDE" version))
              (sha256
               (base32
                "1dmg0q4sp2d2anzhw2my8xjhpyjsx0kf7r202q5bkw8yr57jnhvr"))))
    (properties `((upstream-name . "AutoregressionMDE")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=AutoregressionMDE")
    (synopsis "Minimum Distance Estimation in Autoregressive Model")
    (description
     "Consider autoregressive model of order p where the distribution function of
innovation is unknown, but innovations are independent and symmetrically
distributed.  The package contains a function named ARMDE which takes X (vector
of n observations) and p (order of the model) as input argument and returns
minimum distance estimator of the parameters in the model.")
    (license license:gpl2)))

(define-public r-autoreg
  (package
    (name "r-autoreg")
    (version "0.2.6")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "autoReg" version))
              (sha256
               (base32
                "1jgk6gkqz4fm2xznbvxj334b5bc7i2hkpz6jn8k31l3y8c5fzqcz"))))
    (properties `((upstream-name . "autoReg")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-tidycmprsk
                             r-survival
                             r-stringr
                             r-scales
                             r-rlang
                             r-purrr
                             r-patchwork
                             r-pammtools
                             r-officer
                             r-nortest
                             r-moonbook
                             r-mice
                             r-maxstat
                             r-ggplot2
                             r-flextable
                             r-dplyr
                             r-crayon
                             r-broom
                             r-boot))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/cardiomoon/autoReg")
    (synopsis "Automatic Linear and Logistic Regression and Survival Analysis")
    (description
     "Make summary tables for descriptive statistics and select explanatory variables
automatically in various regression models.  Support linear models, generalized
linear models and cox-proportional hazard models.  Generate publication-ready
tables summarizing result of regression analysis and plots.  The tables and
plots can be exported in \"HTML\", \"pdf('LaTex')\", \"docx('MS Word')\" and \"pptx('MS
Powerpoint')\" documents.")
    (license license:gpl3)))

(define-public r-autorasch
  (package
    (name "r-autorasch")
    (version "0.2.2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "autoRasch" version))
              (sha256
               (base32
                "15vgmpvcw7hi1i5kaqj9q126qmfa54h8ay9w6wa7yxjbginp9v7c"))))
    (properties `((upstream-name . "autoRasch")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpparmadillo r-rcpp r-lavaan r-foreach
                             r-doparallel))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=autoRasch")
    (synopsis "Semi-Automated Rasch Analysis")
    (description
     "This package performs Rasch analysis (semi-)automatically, which has been shown
to be comparable with the standard Rasch analysis (Feri Wijayanto et al. (2021)
<doi:10.1111/bmsp.12218>, Feri Wijayanto et al. (2022)
<doi:10.3758/s13428-022-01947-9>, Feri Wijayanto et al. (2022)
<doi:10.1177/01466216221125178>).")
    (license license:gpl2)))

(define-public r-autoplotprotein
  (package
    (name "r-autoplotprotein")
    (version "1.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "Autoplotprotein" version))
              (sha256
               (base32
                "13mxqmhhdiq7mz4m6nx39dsq7x3bm8fsgskswx48vsq6x2k6byxa"))))
    (properties `((upstream-name . "Autoplotprotein")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml r-seqinr r-plyr r-plotrix r-ade4))
    (home-page "https://cran.r-project.org/package=Autoplotprotein")
    (synopsis "Development of Visualization Tools for Protein Sequence")
    (description
     "The image of the amino acid transform on the protein level is drawn, and the
automatic routing of the functional elements such as the domain and the mutation
site is completed.")
    (license license:gpl3)))

(define-public r-autoplotly
  (package
    (name "r-autoplotly")
    (version "0.1.4")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "autoplotly" version))
              (sha256
               (base32
                "1z577jvadgiz028z7x0786d3qhlkrvv9i34xmllizvg94kxv3bl1"))))
    (properties `((upstream-name . "autoplotly")))
    (build-system r-build-system)
    (propagated-inputs (list r-plotly r-ggplot2 r-ggfortify))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/terrytangyuan/autoplotly")
    (synopsis
     "Automatic Generation of Interactive Visualizations for Statistical Results")
    (description
     "Functionalities to automatically generate interactive visualizations for
statistical results supported by ggfortify', such as time series, PCA,
clustering and survival analysis, with plotly.js <https://plotly.com/> and
ggplot2 style.  The generated visualizations can also be easily extended using
ggplot2 and plotly syntax while staying interactive.")
    (license license:gpl2)))

(define-public r-autopipe
  (package
    (name "r-autopipe")
    (version "0.1.6")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AutoPipe" version))
              (sha256
               (base32
                "0bzllh92fgsmz79lh6m2f10vsx5qng4l7bwbwkp2kzwnncy7cq63"))))
    (properties `((upstream-name . "AutoPipe")))
    (build-system r-build-system)
    (propagated-inputs (list r-siggenes
                             r-rtsne
                             r-rcolorbrewer
                             r-pamr
                             r-org-hs-eg-db
                             r-msigdbr
                             r-fgsea
                             r-consensusclusterplus
                             r-clusterprofiler
                             r-cluster
                             r-annotate))
    (home-page "https://cran.r-project.org/package=AutoPipe")
    (synopsis
     "Automated Transcriptome Classifier Pipeline: Comprehensive Transcriptome Analysis")
    (description
     "An unsupervised fully-automated pipeline for transcriptome analysis or a
supervised option to identify characteristic genes from predefined subclasses.
We rely on the pamr
<http://www.bioconductor.org/packages//2.7/bioc/html/pamr.html> clustering
algorithm to cluster the Data and then draw a heatmap of the clusters with the
most significant genes and the least significant genes according to the pamr
algorithm.  This way we get easy to grasp heatmaps that show us for each cluster
which are the clusters most defining genes.")
    (license license:gpl3)))

(define-public r-autonewsmd
  (package
    (name "r-autonewsmd")
    (version "0.0.4")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "autonewsmd" version))
              (sha256
               (base32
                "0bpwg9gr55c9fyj9xhm8hr2zhw2skghqahdw4k2l402kx8aciq1p"))))
    (properties `((upstream-name . "autonewsmd")))
    (build-system r-build-system)
    (propagated-inputs (list r-rmarkdown r-r6 r-magrittr r-git2r r-data-table))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/kapsner/autonewsmd")
    (synopsis "Auto-Generate Changelog using Conventional Commits")
    (description
     "Automatically generate a changelog file (NEWS.md / CHANGELOG.md) from the git
history using conventional commit messages
(<https://www.conventionalcommits.org/en/v1.0.0/>).")
    (license license:gpl3)))

(define-public r-automrp
  (package
    (name "r-automrp")
    (version "1.0.2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "autoMrP" version))
              (sha256
               (base32
                "11r849hglwgbqiq34q7xd3cdli5qrbqh90faj7pdm09sjkk4mn37"))))
    (properties `((upstream-name . "autoMrP")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-tibble
                             r-rlang
                             r-r-rsp
                             r-purrr
                             r-lme4
                             r-knitr
                             r-glmmlasso
                             r-ggplot2
                             r-gbm
                             r-foreach
                             r-forcats
                             r-ebmaforecast
                             r-e1071
                             r-dplyr
                             r-dorng
                             r-doparallel))
    (home-page "https://github.com/retowuest/autoMrP")
    (synopsis "Improving MrP with Ensemble Learning")
    (description
     "This package provides a tool that improves the prediction performance of
multilevel regression with post-stratification (MrP) by combining a number of
machine learning methods.  For information on the method, please refer to
Broniecki, Wüest, Leemann (2020) Improving Multilevel Regression with
Post-Stratification Through Machine Learning (autoMrP) forthcoming in Journal of
Politics'.  Final pre-print version:
<https://lucasleemann.files.wordpress.com/2020/07/automrp-r2pa.pdf>.")
    (license license:gpl3)))

(define-public r-automl
  (package
    (name "r-automl")
    (version "1.3.2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "automl" version))
              (sha256
               (base32
                "1nrg8q3y6rv69nmnsylg8rps4b4prx46j5a8ljlr24yc34504ck3"))))
    (properties `((upstream-name . "automl")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=automl")
    (synopsis "Deep Learning with Metaheuristic")
    (description
     "Fits from simple regression to highly customizable deep neural networks either
with gradient descent or metaheuristic, using automatic hyper parameters tuning
and custom cost function.  A mix inspired by the common tricks on Deep Learning
and Particle Swarm Optimization.")
    (license (list license:gpl2+ license:gpl3+))))

(define-public r-automfa
  (package
    (name "r-automfa")
    (version "1.0.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "autoMFA" version))
              (sha256
               (base32
                "1sbcl38cq7y7hln1qffk5s71xgg9hs7dlwyvynqf96z2z2421pw4"))))
    (properties `((upstream-name . "autoMFA")))
    (build-system r-build-system)
    (propagated-inputs (list r-usethis
                             r-rfast
                             r-rdpack
                             r-pracma
                             r-matrix
                             r-mass
                             r-expm
                             r-abind))
    (home-page "https://cran.r-project.org/package=autoMFA")
    (synopsis "Algorithms for Automatically Fitting MFA Models")
    (description
     "This package provides methods for fitting the Mixture of Factor Analyzers (MFA)
model automatically.  The MFA model is a mixture model where each sub-population
is assumed to follow the Factor Analysis model.  The Factor Analysis (FA) model
is a latent variable model which assumes that observations are normally
distributed, but imposes constraints on their covariance matrix.  The MFA model
contains two hyperparameters; g (the number of components in the mixture) and q
(the number of factors in each component Factor Analysis model).  Usually, the
Expectation-Maximisation algorithm would be used to fit the MFA model, but this
requires g and q to be known.  This package treats g and q as unknowns and
provides several methods which infer these values with as little input from the
user as possible.")
    (license license:gpl3+)))

(define-public r-automagic
  (package
    (name "r-automagic")
    (version "0.5.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "automagic" version))
              (sha256
               (base32
                "1mmm6kj6mxrn3s4v8ryszkxr9z7bh9cvhin7xjq111fkwly7wjkq"))))
    (properties `((upstream-name . "automagic")))
    (build-system r-build-system)
    (propagated-inputs (list r-yaml
                             r-remotes
                             r-purrr
                             r-magrittr
                             r-knitr
                             r-formatr
                             r-dplyr))
    (home-page "https://github.com/cole-brokamp/automagic")
    (synopsis
     "Automagically Document and Install Packages Necessary to Run R Code")
    (description
     "Parse R code in a given directory for R packages and attempt to install them
from CRAN or GitHub.  Optionally use a dependencies file for tighter control
over which package versions to install.")
    (license (list license:gpl2+ license:gpl3+))))

(define-public r-autokeras
  (package
    (name "r-autokeras")
    (version "1.0.12")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "autokeras" version))
              (sha256
               (base32
                "0wyqz40fc277z1q1zxdmmjzksnmlh58r27a6hx08h6hmzvng5avy"))))
    (properties `((upstream-name . "autokeras")))
    (build-system r-build-system)
    (propagated-inputs (list r-reticulate r-keras))
    (home-page "https://github.com/r-tensorflow/autokeras")
    (synopsis "R Interface to 'AutoKeras'")
    (description
     "R Interface to AutoKeras <https://autokeras.com/>.  AutoKeras is an open source
software library for Automated Machine Learning (AutoML).  The ultimate goal of
AutoML is to provide easily accessible deep learning tools to domain experts
with limited data science or machine learning background.  AutoKeras provides
functions to automatically search for architecture and hyperparameters of deep
learning models.")
    (license license:expat)))

(define-public r-autoimage
  (package
    (name "r-autoimage")
    (version "2.2.3")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "autoimage" version))
              (sha256
               (base32
                "1jhkd7mbig6wpyc69iynfrj5i62lrwcwqbgjkmq8b9p5raglm1g2"))))
    (properties `((upstream-name . "autoimage")))
    (build-system r-build-system)
    (propagated-inputs (list r-mba
                             r-maps
                             r-mapproj
                             r-ggplot2
                             r-fields
                             r-colorspace))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=autoimage")
    (synopsis "Multiple Heat Maps for Projected Coordinates")
    (description
     "This package provides functions for displaying multiple images or scatterplots
with a color scale, i.e., heat maps, possibly with projected coordinates.  The
package relies on the base graphics system, so graphics are rendered rapidly.")
    (license license:gpl2+)))

(define-public r-autohrf
  (package
    (name "r-autohrf")
    (version "1.1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "autohrf" version))
              (sha256
               (base32
                "1zmnrfak91q10aa9a3i816hln2skvbnamigcbsc1dbkj0j6mdqwd"))))
    (properties `((upstream-name . "autohrf")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcolorbrewer
                             r-magrittr
                             r-lubridate
                             r-gtools
                             r-ggplot2
                             r-foreach
                             r-dplyr
                             r-doparallel
                             r-cowplot))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/demsarjure/autohrf")
    (synopsis
     "Automated Generation of Data-Informed GLM Models in Task-Based fMRI Data Analysis")
    (description
     "Analysis of task-related functional magnetic resonance imaging (fMRI) activity
at the level of individual participants is commonly based on general linear
modelling (GLM) that allows us to estimate to what extent the blood oxygenation
level dependent (BOLD) signal can be explained by task response predictors
specified in the GLM model.  The predictors are constructed by convolving the
hypothesised timecourse of neural activity with an assumed hemodynamic response
function (HRF).  To get valid and precise estimates of task response, it is
important to construct a model of neural activity that best matches actual
neuronal activity.  The construction of models is most often driven by
predefined assumptions on the components of brain activity and their duration
based on the task design and specific aims of the study.  However, our
assumptions about the onset and duration of component processes might be wrong
and can also differ across brain regions.  This can result in inappropriate or
suboptimal models, bad fitting of the model to the actual data and invalid
estimations of brain activity.  Here we present an approach in which
theoretically driven models of task response are used to define constraints
based on which the final model is derived computationally using the actual data.
 Specifically, we developed autohrf — a package for the R programming language
that allows for data-driven estimation of HRF models.  The package uses genetic
algorithms to efficiently search for models that fit the underlying data well.
The package uses automated parameter search to find the onset and duration of
task predictors which result in the highest fitness of the resulting GLM based
on the fMRI signal under predefined restrictions.  We evaluate the usefulness of
the autohrf package on publicly available datasets of task-related fMRI
activity.  Our results suggest that by using autohrf users can find better task
related brain activity models in a quick and efficient manner.")
    (license license:gpl3+)))

(define-public r-autoharp
  (package
    (name "r-autoharp")
    (version "0.0.10")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "autoharp" version))
              (sha256
               (base32
                "0jn7nya4lb1pvdy7yyimxga4gn042jqwl3w82m6c244kqydm5fi0"))))
    (properties `((upstream-name . "autoharp")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-tibble
                             r-stringr
                             r-shiny
                             r-rmarkdown
                             r-rlang
                             r-pryr
                             r-magrittr
                             r-lintr
                             r-knitr
                             r-igraph
                             r-dplyr))
    (home-page "https://singator.github.io/autoharp-docs/")
    (synopsis "Semi-Automatic Grading of R and Rmd Scripts")
    (description
     "This package provides a customisable set of tools for assessing and grading R or
R-markdown scripts from students.  It allows for checking correctness of code
output, runtime statistics and static code analysis.  The latter feature is made
possible by representing R expressions using a tree structure.")
    (license license:expat)))

(define-public r-autofrk
  (package
    (name "r-autofrk")
    (version "1.4.3")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "autoFRK" version))
              (sha256
               (base32
                "1k3h2gsck06dnvrifg9rhxi6b3fwfjrkvg0q2wzb9kdnnzgiwcln"))))
    (properties `((upstream-name . "autoFRK")))
    (build-system r-build-system)
    (propagated-inputs (list r-spam
                             r-rspectra
                             r-rcppparallel
                             r-rcppeigen
                             r-rcpp
                             r-mgcv
                             r-mass
                             r-latticekrig
                             r-fnn
                             r-filematrix
                             r-filehashsqlite
                             r-filehash
                             r-fields))
    (home-page "https://cran.r-project.org/package=autoFRK")
    (synopsis "Automatic Fixed Rank Kriging")
    (description
     "Automatic fixed rank kriging for (irregularly located) spatial data using a
class of basis functions with multi-resolution features and ordered in terms of
their resolutions.  The model parameters are estimated by maximum likelihood
(ML) and the number of basis functions is determined by Akaike's information
criterion (AIC).  For spatial data with either one realization or independent
replicates, the ML estimates and AIC are efficiently computed using their
closed-form expressions when no missing value occurs.  Details regarding the
basis function construction, parameter estimation, and AIC calculation can be
found in Tzeng and Huang (2018) <doi:10.1080/00401706.2017.1345701>.  For data
with missing values, the ML estimates are obtained using the expectation-
maximization algorithm.  Apart from the number of basis functions, there are no
other tuning parameters, making the method fully automatic.  Users can also
include a stationary structure in the spatial covariance, which utilizes
LatticeKrig package.")
    (license license:gpl2+)))

(define-public r-autofc
  (package
    (name "r-autofc")
    (version "0.1.2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "autoFC" version))
              (sha256
               (base32
                "1hxpmd753qpzlyjivn37m1kij3gpp9x6xyw1x6090h9n4girnya2"))))
    (properties `((upstream-name . "autoFC")))
    (build-system r-build-system)
    (propagated-inputs (list r-irrcac))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/tspsyched/autoFC")
    (synopsis "Automatic Construction of Forced-Choice Tests")
    (description
     "Forced-choice (FC) response has gained increasing popularity and interest for
its resistance to faking when well-designed (Cao & Drasgow, 2019
<doi:10.1037/apl0000414>).  To established well-designed FC scales, typically
each item within a block should measure different trait and have similar level
of social desirability (Zhang et al., 2020 <doi:10.1177/1094428119836486>).
Recent study also suggests the importance of high inter-item agreement of social
desirability between items within a block (Pavlov et al., 2021
<doi:10.31234/osf.io/hmnrc>).  In addition to this, FC developers may also need
to maximize factor loading differences (Brown & Maydeu-Olivares, 2011
<doi:10.1177/0013164410375112>) or minimize item location differences (Cao &
Drasgow, 2019 <doi:10.1037/apl0000414>) depending on scoring models.  Decision
of which items should be assigned to the same block, termed item pairing, is
thus critical to the quality of an FC test.  This pairing process is essentially
an optimization process which is currently carried out manually.  However, given
that we often need to simultaneously meet multiple objectives, manual pairing
becomes impractical or even not feasible once the number of latent traits and/or
number of items per trait are relatively large.  To address these problems,
autoFC is developed as a practical tool for facilitating the automatic
construction of FC tests, essentially exempting users from the burden of manual
item pairing and reducing the computational costs and biases induced by simple
ranking methods.  Given characteristics of each item (and item responses), FC
tests can be automatically constructed based on user-defined pairing criteria
and weights as well as customized optimization behavior.  Users can also
construct parallel forms of the same test following the same pairing rules.")
    (license license:gpl3)))

(define-public r-autoencoder
  (package
    (name "r-autoencoder")
    (version "1.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "autoencoder" version))
              (sha256
               (base32
                "0ly1aanayk28nx6yqfhl7d0zm4vg6rfjikf5ibn8zhmkrfyflj1y"))))
    (properties `((upstream-name . "autoencoder")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=autoencoder")
    (synopsis
     "Sparse Autoencoder for Automatic Learning of Representative Features from Unlabeled Data")
    (description
     "Implementation of the sparse autoencoder in R environment, following the notes
of Andrew Ng
(http://www.stanford.edu/class/archive/cs/cs294a/cs294a.1104/sparseAutoencoder.pdf).
 The features learned by the hidden layer of the autoencoder (through
unsupervised learning of unlabeled data) can be used in constructing deep belief
neural networks.")
    (license license:gpl2)))

(define-public r-autodeskr
  (package
    (name "r-autodeskr")
    (version "0.1.3")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AutoDeskR" version))
              (sha256
               (base32
                "1n7c8ris8b517bs1wahpvrhwfbvn2q4jbq01kgiv9lfmkjckzfkc"))))
    (properties `((upstream-name . "AutoDeskR")))
    (build-system r-build-system)
    (propagated-inputs (list r-shiny r-jsonlite r-httr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/paulgovan/autodeskr")
    (synopsis "An Interface to the 'AutoDesk' 'API' Platform")
    (description
     "An interface to the AutoDesk API Platform including the Authentication API for
obtaining authentication to the AutoDesk Forge Platform, Data Management API for
managing data across the platform's cloud services, Design Automation API for
performing automated tasks on design files in the cloud, Model Derivative API
for translating design files into different formats, sending them to the viewer
app, and extracting design data, and Viewer for rendering 2D and 3D models (see
<https://developer.autodesk.com> for more information).")
    (license (list (license:fsdg-compatible "Apache License")
                   (license:fsdg-compatible "file://LICENSE")))))

(define-public r-autocovariateselection
  (package
    (name "r-autocovariateselection")
    (version "1.0.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "autoCovariateSelection" version))
              (sha256
               (base32
                "0s9ar7bmw0n84hvavp63zhm6769l9p88md0kqqcxl0mw67j8q930"))))
    (properties `((upstream-name . "autoCovariateSelection")))
    (build-system r-build-system)
    (propagated-inputs (list r-purrr r-dplyr r-data-table))
    (home-page "https://github.com/technOslerphile/autoCovariateSelection")
    (synopsis "Automated Covariate Selection Using HDPS Algorithm")
    (description
     "This package contains functions to implement automated covariate selection using
methods described in the high-dimensional propensity score (HDPS) algorithm by
Schneeweiss et.al.  Covariate adjustment in real-world-observational-data (RWD)
is important for for estimating adjusted outcomes and this can be done by using
methods such as, but not limited to, propensity score matching, propensity score
weighting and regression analysis.  While these methods strive to statistically
adjust for confounding, the major challenge is in selecting the potential
covariates that can bias the outcomes comparison estimates in observational RWD
(Real-World-Data).  This is where the utility of automated covariate selection
comes in.  The functions in this package help to implement the three major steps
of automated covariate selection as described by Schneeweiss et.  al elsewhere.
These three functions, in order of the steps required to execute automated
covariate selection are, get_candidate_covariates(), get_recurrence_covariates()
and get_prioritised_covariates().  In addition to these functions, a sample
real-world-data from publicly available de-identified medical claims data is
also available for running examples and also for further exploration.  The
original article where the algorithm is described by Schneeweiss et.al. (2009)
<doi:10.1097/EDE.0b013e3181a663cc> .")
    (license license:expat)))

(define-public r-autocogs
  (package
    (name "r-autocogs")
    (version "0.1.4")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "autocogs" version))
              (sha256
               (base32
                "0v27l9a0ysj7x9wjka1jl1bq9rmxmzldclcp1w59a6807wjlszhx"))))
    (properties `((upstream-name . "autocogs")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble
                             r-progress
                             r-moments
                             r-mclust
                             r-mass
                             r-hexbin
                             r-ggplot2
                             r-dplyr
                             r-diptest
                             r-checkmate
                             r-broom))
    (home-page "https://github.com/schloerke/autocogs")
    (synopsis "Automatic Cognostic Summaries")
    (description
     "Automatically calculates cognostic groups for plot objects and list column plot
objects.  Results are returned in a nested data frame.")
    (license license:expat)))

(define-public r-autocart
  (package
    (name "r-autocart")
    (version "1.4.5")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "autocart" version))
              (sha256
               (base32
                "1zgcmrm4dkdnr130hwwka2nwdczgvc3jc9hxrb6nfs8ijb24gl36"))))
    (properties `((upstream-name . "autocart")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcppparallel r-rcpparmadillo r-rcpp r-mgcv
                             r-fields))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=autocart")
    (synopsis "Autocorrelation Regression Trees")
    (description
     "This package provides a modified version of the classification and regression
tree (CART) algorithm for modelling spatial data that features coordinate
information.  Coordinate information can be used to evaluate measures of spatial
autocorrelation and spatial compactness during the splitting phase of the tree,
leading to better predictions and more physically realistic predictions on these
types of datasets.  These methods are described in Ancell and Bean (2021)
<arXiv:2101.08258>.")
    (license license:expat)))

(define-public r-autobagging
  (package
    (name "r-autobagging")
    (version "0.1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "autoBagging" version))
              (sha256
               (base32
                "01k44rgkpbbr3m2x360aq0fz2qi7nz036g5dsh2y3jy94rmddbyy"))))
    (properties `((upstream-name . "autoBagging")))
    (build-system r-build-system)
    (propagated-inputs (list r-xgboost
                             r-rpart
                             r-party
                             r-minerva
                             r-mass
                             r-lsr
                             r-infotheo
                             r-entropy
                             r-e1071
                             r-corelearn
                             r-cluster
                             r-caret
                             r-abind))
    (home-page "https://cran.r-project.org/package=autoBagging")
    (synopsis "Learning to Rank Bagging Workflows with Metalearning")
    (description
     "This package provides a framework for automated machine learning.  Concretely,
the focus is on the optimisation of bagging workflows.  A bagging workflows is
composed by three phases: (i) generation: which and how many predictive models
to learn; (ii) pruning: after learning a set of models, the worst ones are cut
off from the ensemble; and (iii) integration: how the models are combined for
predicting a new observation.  autoBagging optimises these processes by
combining metalearning and a learning to rank approach to learn from metadata.
It automatically ranks 63 bagging workflows by exploiting past performance and
dataset characterization.  A complete description of the method can be found in:
Pinto, F., Cerqueira, V., Soares, C., Mendes-Moreira, J. (2017): \"autoBagging:
Learning to Rank Bagging Workflows with Metalearning\" arXiv preprint
arXiv:1706.09367.")
    (license license:gpl2+)))

(define-public r-auto-pca
  (package
    (name "r-auto-pca")
    (version "0.3")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "auto.pca" version))
              (sha256
               (base32
                "01m2ldpcxzj7fhgmr9wp4ha3gqdyh7l5bkrnw83smcbq5229hsyy"))))
    (properties `((upstream-name . "auto.pca")))
    (build-system r-build-system)
    (propagated-inputs (list r-psych r-plyr))
    (home-page "https://cran.r-project.org/package=auto.pca")
    (synopsis
     "Automatic Variable Reduction Using Principal Component Analysis")
    (description
     "PCA done by eigenvalue decomposition of a data correlation matrix, here it
automatically determines the number of factors by eigenvalue greater than 1 and
it gives the uncorrelated variables based on the rotated component scores, Such
that in each principal component variable which has the high variance are
selected.  It will be useful for non-statisticians in selection of variables.
For more information, see the
<http://www.ijcem.org/papers032013/ijcem_032013_06.pdf> web page.")
    (license license:gpl2)))

(define-public r-auth0
  (package
    (name "r-auth0")
    (version "0.2.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "auth0" version))
              (sha256
               (base32
                "077nqh28q3b9jb25fy0157l06zpx3x0rg4z5dz2dqsh88xy4nhqj"))))
    (properties `((upstream-name . "auth0")))
    (build-system r-build-system)
    (propagated-inputs (list r-yaml r-shinyjs r-shiny r-httr r-htmltools))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=auth0")
    (synopsis "Secure Authentication in Shiny with Auth0")
    (description
     "Uses Auth0 API (see <https://auth0.com> for more information) to use a simple
and secure authentication system.  It provides tools to log in and out a shiny
application using social networks or a list of e-mails.")
    (license license:expat)))

(define-public r-autests
  (package
    (name "r-autests")
    (version "0.99")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AUtests" version))
              (sha256
               (base32
                "0ima350mjlqvij6f9xy6wfcibvlji7nh0prpqngj7apn82ri4m2k"))))
    (properties `((upstream-name . "AUtests")))
    (build-system r-build-system)
    (propagated-inputs (list r-logistf))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=AUtests")
    (synopsis "Approximate Unconditional and Permutation Tests")
    (description
     "This package performs approximate unconditional and permutation testing for 2x2
contingency tables.  Motivated by testing for disease association with rare
genetic variants in case-control studies.  When variants are extremely rare,
these tests give better control of Type I error than standard tests.")
    (license license:gpl2)))

(define-public r-australianpoliticians
  (package
    (name "r-australianpoliticians")
    (version "0.1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AustralianPoliticians" version))
              (sha256
               (base32
                "1ws0fry00xckxgbagp069fcmnbcrcnsvs9v5jizp1xs791ij0njv"))))
    (properties `((upstream-name . "AustralianPoliticians")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble r-readr r-purrr r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/RohanAlexander/AustralianPoliticians")
    (synopsis "Provides Datasets About Australian Politicians")
    (description
     "This package provides access to biographical and political data about Australian
federal politicians who served between 1901 and 2021.  This enhances how
reproducible research is that uses this data.")
    (license license:expat)))

(define-public r-ausplotsr
  (package
    (name "r-ausplotsr")
    (version "1.2.7")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ausplotsR" version))
              (sha256
               (base32
                "0vlldbdbgplk6a9n2xkac8i5nxf0y2p4zbrw5q9a3qc71zfl33yj"))))
    (properties `((upstream-name . "ausplotsR")))
    (build-system r-build-system)
    (propagated-inputs (list r-vegan
                             r-sp
                             r-r-utils
                             r-plyr
                             r-maptools
                             r-maps
                             r-mapdata
                             r-jsonlite
                             r-jose
                             r-httr
                             r-gtools
                             r-ggplot2
                             r-curl
                             r-betapart))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=ausplotsR")
    (synopsis "TERN AusPlots Analysis Package")
    (description
     "Extraction, preparation, visualisation and analysis of TERN AusPlots ecosystem
monitoring data.  Direct access to plot-based data on vegetation and soils
across Australia, including physical sample barcode numbers.  Simple function
calls extract the data and merge them into species occurrence matrices for
downstream analysis, or calculate things like basal area and fractional cover.
TERN AusPlots is a national field plot-based ecosystem surveillance monitoring
method and dataset for Australia.  The data have been collected across a
national network of plots and transects by the Terrestrial Ecosystem Research
Network (TERN - <https://www.tern.org.au>), an Australian Government
NCRIS-enabled project, and its Ecosystem Surveillance platform
(<https://www.tern.org.au/tern-observatory/tern-ecosystem-surveillance/>).")
    (license license:gpl3)))

(define-public r-auroc
  (package
    (name "r-auroc")
    (version "0.2-1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "auRoc" version))
              (sha256
               (base32
                "152jdvzigcplii5amj0mnral3g2jyy3rfsc745mx36sspw1396yx"))))
    (properties `((upstream-name . "auRoc")))
    (build-system r-build-system)
    (propagated-inputs (list r-rjags r-probyx r-mbess r-coda))
    (home-page "https://cran.r-project.org/package=auRoc")
    (synopsis "Various Methods to Estimate the AUC")
    (description
     "Estimate the AUC using a variety of methods as follows: (1) frequentist
nonparametric methods based on the Mann-Whitney statistic or kernel methods. (2)
frequentist parametric methods using the likelihood ratio test based on
higher-order asymptotic results, the signed log-likelihood ratio test, the Wald
test, or the approximate t solution to the Behrens-Fisher problem. (3) Bayesian
parametric MCMC methods.")
    (license (list license:gpl2+ license:gpl3+))))

(define-public r-aurielshgaussian
  (package
    (name "r-aurielshgaussian")
    (version "0.2.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AurieLSHGaussian" version))
              (sha256
               (base32
                "0dzwqv396inbx4r6758vr4gip1y42ahavspadgm4xhafvipg73rb"))))
    (properties `((upstream-name . "AurieLSHGaussian")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringdist r-reshape2 r-lsa r-igraph
                             r-flexclust))
    (home-page "https://cran.r-project.org/package=AurieLSHGaussian")
    (synopsis
     "Creates a Neighbourhood Using Locality Sensitive Hashing for Gaussian Projections")
    (description
     "Uses locality sensitive hashing and creates a neighbourhood graph for a data set
and calculates the adjusted rank index value for the same.  It uses Gaussian
random planes to decide the nature of a given point.  Datar, Mayur, Nicole
Immorlica, Piotr Indyk, and Vahab S. Mirrokni(2004) <doi:10.1145/997817.997857>.")
    (license license:gpl2)))

(define-public r-aum
  (package
    (name "r-aum")
    (version "2022.2.7")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "aum" version))
              (sha256
               (base32
                "0a2nh1fnn7z4c592gj280w8yb54wi8msfdmg8gzbz52m1x3pxbi0"))))
    (properties `((upstream-name . "aum")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpp r-data-table))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/tdhock/aum")
    (synopsis "Area Under Minimum of False Positives and Negatives")
    (description
     "Standard template library sort is used to implement an efficient algorithm
<arXiv:2107.01285> for computing Area Under Minimum and directional derivatives.")
    (license license:gpl3)))

(define-public r-auk
  (package
    (name "r-auk")
    (version "0.6.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "auk" version))
              (sha256
               (base32
                "1l37izfjsypq2pbbifajilhi00fpbjdkpp6ahy3nxfsc7v22ldwr"))))
    (properties `((upstream-name . "auk")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-stringr
                             r-stringi
                             r-rlang
                             r-readr
                             r-magrittr
                             r-httr
                             r-dplyr
                             r-countrycode
                             r-assertthat))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/CornellLabofOrnithology/auk")
    (synopsis "eBird Data Extraction and Processing in R")
    (description
     "Extract and process bird sightings records from eBird (<http://ebird.org>), an
online tool for recording bird observations.  Public access to the full eBird
database is via the eBird Basic Dataset (EBD; see
<http://ebird.org/ebird/data/download> for access), a downloadable text file.
This package is an interface to AWK for extracting data from the EBD based on
taxonomic, spatial, or temporal filters, to produce a manageable file size that
can be imported into R.")
    (license license:gpl3)))

(define-public r-augsimex
  (package
    (name "r-augsimex")
    (version "3.7.4")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "augSIMEX" version))
              (sha256
               (base32
                "0620yxqi160ar91shl5macn890zpc60c9nqy4w8i6m7sskv6gl3z"))))
    (properties `((upstream-name . "augSIMEX")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpp r-nleqslv r-mass r-formula))
    (home-page "https://cran.r-project.org/package=augSIMEX")
    (synopsis
     "Analysis of Data with Mixed Measurement Error and Misclassification in Covariates")
    (description
     "Implementation of the augmented Simulation-Extrapolation (SIMEX) algorithm
proposed by Yi et al. (2015) <doi:10.1080/01621459.2014.922777> for analyzing
the data with mixed measurement error and misclassification.  The main function
provides a similar summary output as that of glm() function.  Both parametric
and empirical SIMEX are considered in the package.")
    (license license:gpl2+)))

(define-public r-augmenterr
  (package
    (name "r-augmenterr")
    (version "0.1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AugmenterR" version))
              (sha256
               (base32
                "0hi501p8ksaqzc9dq16dbmkz50kakgw3k0awdkbpci5can2sqvfl"))))
    (properties `((upstream-name . "AugmenterR")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=AugmenterR")
    (synopsis "Data Augmentation for Machine Learning on Tabular Data")
    (description
     "Implementation of a data augmentation technique based on conditional entropy It
was devised by both authors during their masters and is discussed in detail in
the second author dissertation.  It is able to create novel samples conditioned
on a desired value of a categorical attribute, as a way to augment data for
classification tasks Tests discussed in the dissertation and future paper
present that the technique satisfies several statistical assumptions for the
novel samples.  It also shows significant improvement for machine learning
models trained on small data.")
    (license license:expat)))

(define-public r-augmentedrcbd
  (package
    (name "r-augmentedrcbd")
    (version "0.1.5")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "augmentedRCBD" version))
              (sha256
               (base32
                "1bfb1jqakghf1nb3zwzf69cywwxwr1whzvyig8g3qa8ciq5f1h3i"))))
    (properties `((upstream-name . "augmentedRCBD")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringi
                             r-reshape2
                             r-rdpack
                             r-officer
                             r-multcompview
                             r-multcomp
                             r-moments
                             r-mathjaxr
                             r-ggplot2
                             r-flextable
                             r-emmeans
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=augmentedRCBD")
    (synopsis "Analysis of Augmented Randomised Complete Block Designs")
    (description
     "This package provides functions for analysis of data generated from experiments
in augmented randomised complete block design according to Federer, W.T. (1961)
<doi:10.2307/2527837>.  Computes analysis of variance, adjusted means,
descriptive statistics, genetic variability statistics etc.  Further includes
data visualization and report generation functions.")
    (license (list license:gpl2 license:gpl3))))

(define-public r-audubon
  (package
    (name "r-audubon")
    (version "0.3.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "audubon" version))
              (sha256
               (base32
                "0mswnghq46s41zcyvk5ksrbx2f2zm8dap4df1k1377d7nmjb1rgl"))))
    (properties `((upstream-name . "audubon")))
    (build-system r-build-system)
    (propagated-inputs (list r-v8
                             r-tidyselect
                             r-stringi
                             r-rlang
                             r-readr
                             r-purrr
                             r-memoise
                             r-magrittr
                             r-dplyr))
    (home-page "https://github.com/paithiov909/audubon")
    (synopsis "Japanese Text Processing Tools")
    (description
     "This package provides a collection of Japanese text processing tools for filling
Japanese iteration marks, Japanese character type conversions, segmentation by
phrase, and text normalization which is based on rules for the Sudachi
morphological analyzer and the NEologd (Neologism dictionary for MeCab').  These
features are specific to Japanese and are not implemented in ICU (International
Components for Unicode).")
    (license (license:fsdg-compatible "Apache License (>= 2)"))))

(define-public r-audrex
  (package
    (name "r-audrex")
    (version "2.0.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "audrex" version))
              (sha256
               (base32
                "1ifijkbqvdjp1si14p80mbqhq7sby8qgzr181agm3da1nkmic3vp"))))
    (properties `((upstream-name . "audrex")))
    (build-system r-build-system)
    (propagated-inputs (list r-xgboost
                             r-tictoc
                             r-stringr
                             r-scales
                             r-readr
                             r-rbayesianoptimization
                             r-purrr
                             r-narray
                             r-moments
                             r-modeest
                             r-metrics
                             r-lubridate
                             r-imputets
                             r-ggplot2
                             r-fancova))
    (home-page "https://rpubs.com/giancarlo_vercellino/audrex")
    (synopsis "Automatic Dynamic Regression using Extreme Gradient Boosting")
    (description
     "Dynamic regression for time series using Extreme Gradient Boosting with
hyper-parameter tuning via Bayesian Optimization or Random Search.")
    (license license:gpl3)))

(define-public r-auditor
  (package
    (name "r-auditor")
    (version "1.3.3")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "auditor" version))
              (sha256
               (base32
                "1y6qpbc78yv2w1y9p0mczv69s661i9n2y0x09c5p3hdka7km662w"))))
    (properties `((upstream-name . "auditor")))
    (build-system r-build-system)
    (propagated-inputs (list r-scales
                             r-hnp
                             r-gridextra
                             r-ggrepel
                             r-ggplot2
                             r-dalex))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/ModelOriented/auditor")
    (synopsis "Model Audit - Verification, Validation, and Error Analysis")
    (description
     "This package provides an easy to use unified interface for creating validation
plots for any model.  The auditor helps to avoid repetitive work consisting of
writing code needed to create residual plots.  This visualizations allow to
asses and compare the goodness of fit, performance, and similarity of models.")
    (license (list license:gpl2+ license:gpl3+))))

(define-public r-audit
  (package
    (name "r-audit")
    (version "0.1-2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "audit" version))
              (sha256
               (base32
                "0c8b94a5am196sbvmjxya7cg4aq6fcxr8c958fxx3jmy9r4hn6s2"))))
    (properties `((upstream-name . "audit")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=audit")
    (synopsis "Bounds for Accounting Populations")
    (description
     "Find an upper bound for the total amount of overstatement of assets in a set of
accounts, or estimate the amount of sales tax owed on a collection of
transactions (Meeden and Sargent, 2007, <doi:10.1080/03610920701386802>).")
    (license license:expat)))

(define-public r-audiometry
  (package
    (name "r-audiometry")
    (version "0.3.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "audiometry" version))
              (sha256
               (base32
                "0v6lhkm298xgdny0fhpldfwj8s4ljr21w6y6sv3vvyl87qjgwx8i"))))
    (properties `((upstream-name . "audiometry")))
    (build-system r-build-system)
    (propagated-inputs (list r-ggplot2))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=audiometry")
    (synopsis "Standard Conform Pure Tone Audiometry (PTA) Plots")
    (description
     "Facilitates plotting audiometric data (mostly) by preparing the coordinate
system according to standards, given e.  g.  in American Speech-Language-Hearing
Association (2005), <doi:10.1044/policy.GL2005-00014>.")
    (license license:gpl3)))

(define-public r-audio
  (package
    (name "r-audio")
    (version "0.1-10")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "audio" version))
              (sha256
               (base32
                "1pf4mwqar15v7y6sq8wkfqnr6rgpq9ywwsahzr76n6klijl33iw2"))))
    (properties `((upstream-name . "audio")))
    (build-system r-build-system)
    (native-inputs (list pkg-config))
    (home-page "http://www.rforge.net/audio/")
    (synopsis "Audio Interface for R")
    (description
     "Interfaces to audio devices (mainly sample-based) from R to allow recording and
playback of audio.  Built-in devices include Windows MM, Mac OS X AudioUnits and
PortAudio (the last one is very experimental).")
    (license license:expat)))

(define-public r-auctionr
  (package
    (name "r-auctionr")
    (version "0.1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "auctionr" version))
              (sha256
               (base32
                "0kfx81irqr9mfp4n86z7q5nclcci8vlpvq9zid7miyw3rci7dfvi"))))
    (properties `((upstream-name . "auctionr")))
    (build-system r-build-system)
    (propagated-inputs (list r-numderiv))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/ajmack/auctionr")
    (synopsis "Estimate First-Price Auction Model")
    (description
     "Estimates a first-price auction model with conditionally independent private
values as described in MacKay (2020) <doi:10.2139/ssrn.3096534>.  The model
allows for unobserved heterogeneity that is common to all bidders in addition to
observable heterogeneity.")
    (license license:gpl3)))

(define-public r-auctestr
  (package
    (name "r-auctestr")
    (version "1.0.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "auctestr" version))
              (sha256
               (base32
                "15b1x0c9yhl91gir7jmivp8vxzc8q7wvb0mgam9454avc6l29x4y"))))
    (properties `((upstream-name . "auctestr")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=auctestr")
    (synopsis "Statistical Testing for AUC Data")
    (description
     "This package performs statistical testing to compare predictive models based on
multiple observations of the A statistic (also known as Area Under the Receiver
Operating Characteristic Curve, or AUC).  Specifically, it implements a testing
method based on the equivalence between the A statistic and the Wilcoxon
statistic.  For more information, see Hanley and McNeil (1982)
<doi:10.1148/radiology.143.1.7063747>.")
    (license license:expat)))

(define-public r-attrib
  (package
    (name "r-attrib")
    (version "2021.1.2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "attrib" version))
              (sha256
               (base32
                "17s3hjp8zdl28y4h9iv854y1hli5yg1h0kqhj8v5hms1lhx7c1qq"))))
    (properties `((upstream-name . "attrib")))
    (build-system r-build-system)
    (propagated-inputs (list r-tsmodel
                             r-tibble
                             r-stringr
                             r-progress
                             r-pbs
                             r-mvmeta
                             r-magrittr
                             r-lubridate
                             r-lme4
                             r-glue
                             r-ggplot2
                             r-dlnm
                             r-data-table
                             r-arm))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=attrib")
    (synopsis "Attributable Burden of Disease")
    (description
     "This package provides functions for estimating the attributable burden of
disease due to risk factors.  The posterior simulation is performed using
arm::sim as described in Gelman, Hill (2012) <doi:10.1017/CBO9780511790942> and
the attributable burden method is based on Nielsen, Krause, Molbak
<doi:10.1111/irv.12564>.")
    (license license:expat)))

(define-public r-attenuation
  (package
    (name "r-attenuation")
    (version "1.0.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "attenuation" version))
              (sha256
               (base32
                "0ys4psvkvimmym4qj9cmhq8y7x10kv0x6bsvpjkrsc3l8p2g3474"))))
    (properties `((upstream-name . "attenuation")))
    (build-system r-build-system)
    (home-page "https://github.com/JonasMoss/attenuation/")
    (synopsis "Correcting for Attenuation Due to Measurement Error")
    (description
     "Confidence curves, confidence intervals and p-values for correlation
coefficients corrected for attenuation due to measurement error.  Implements the
methods described in Moss (2019, <arxiv:1911.01576>).")
    (license license:expat)))

(define-public r-attention
  (package
    (name "r-attention")
    (version "0.2.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "attention" version))
              (sha256
               (base32
                "02k156k1yynr82f6rn3pdhc2ngsr0fr6k6rwvi7rhxl37ggh5id7"))))
    (properties `((upstream-name . "attention")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=attention")
    (synopsis "Self-Attention Algorithm")
    (description
     "Self-Attention algorithm helper functions and demonstration vignettes of
increasing depth on how to construct the Self-Attention algorithm, this is based
on Vaswani et al. (2017) <doi:10.48550/arXiv.1706.03762>, Dan Jurafsky and James
H. Martin (2022, ISBN:978-0131873216) <https://web.stanford.edu/~jurafsky/slp3/>
\"Speech and Language Processing (3rd ed.)\" and Alex Graves (2020)
<https://www.youtube.com/watch?v=AIiwuClvH6k> \"Attention and Memory in Deep
Learning\".")
    (license license:gpl3+)))

(define-public r-attempt
  (package
    (name "r-attempt")
    (version "0.3.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "attempt" version))
              (sha256
               (base32
                "1ylgg7jcp8wqmxgf1mydnvh26k0mr8jyjla4hw06730r40yrs58m"))))
    (properties `((upstream-name . "attempt")))
    (build-system r-build-system)
    (propagated-inputs (list r-rlang))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/ColinFay/attempt")
    (synopsis "Tools for Defensive Programming")
    (description
     "Tools for defensive programming, inspired by purrr mappers and based on
rlang'.'attempt extends and facilitates defensive programming by providing a
consistent grammar, and provides a set of easy to use functions for common tests
and conditions.  attempt only depends on rlang', and focuses on speed, so it can
be easily integrated in other functions and used in data analysis.")
    (license license:expat)))

(define-public r-attachment
  (package
    (name "r-attachment")
    (version "0.3.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "attachment" version))
              (sha256
               (base32
                "0rw1dqglnfwhql8342h15xq9qbvcsxd5cvipjvlz827ri428r8r0"))))
    (properties `((upstream-name . "attachment")))
    (build-system r-build-system)
    (propagated-inputs (list r-withr
                             r-stringr
                             r-roxygen2
                             r-rmarkdown
                             r-magrittr
                             r-knitr
                             r-glue
                             r-desc
                             r-cli))
    (native-inputs (list r-knitr))
    (home-page "https://thinkr-open.github.io/attachment/")
    (synopsis "Deal with Dependencies")
    (description
     "Manage dependencies during package development.  This can retrieve all
dependencies that are used in \".R\" files in the \"R/\" directory, in \".Rmd\" files
in \"vignettes/\" directory and in roxygen2 documentation of functions.  There is
a function to update the \"DESCRIPTION\" file of your package with CRAN packages
or any other remote package.  All functions to retrieve dependencies of \".R\"
scripts and \".Rmd\" or \".qmd\" files can be used independently of a package
development.")
    (license license:gpl3)))

(define-public r-atsd
  (package
    (name "r-atsd")
    (version "1.2.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "atsd" version))
              (sha256
               (base32
                "0jan8r5f2r3l2xpdf9rrv4smkr2l645rfdgdfjb1xa54jd3pqvqs"))))
    (properties `((upstream-name . "atsd")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcurl r-httr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/axibase/atsd-api-r/")
    (synopsis "Support Querying Axibase Time-Series Database")
    (description
     "This package provides functions for retrieving time-series and related meta-data
such as entities, metrics, and tags from the Axibase Time-Series Database
(ATSD).  ATSD is a non-relational clustered database used for storing
performance measurements from IT infrastructure resources: servers, network
devices, storage systems, and applications.")
    (license license:asl2.0)))

(define-public r-atsa
  (package
    (name "r-atsa")
    (version "3.1.2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "aTSA" version))
              (sha256
               (base32
                "1p3spas0sxj08hkb8p6k2fy64w86prlw1hbnrqnrklr0hnkg2g54"))))
    (properties `((upstream-name . "aTSA")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=aTSA")
    (synopsis "Alternative Time Series Analysis")
    (description
     "This package contains some tools for testing, analyzing time series data and
fitting popular time series models such as ARIMA, Moving Average and Holt
Winters, etc.  Most functions also provide nice and clear outputs like SAS does,
such as identify, estimate and forecast, which are the same statements in PROC
ARIMA in SAS.")
    (license (list license:gpl2 license:gpl3))))

(define-public r-atr
  (package
    (name "r-atr")
    (version "0.1-1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ATR" version))
              (sha256
               (base32
                "0via7zm3byzbdgrfw351fqvx0g5cj2z31bqfwh7kr99nqgjh0dyn"))))
    (properties `((upstream-name . "ATR")))
    (build-system r-build-system)
    (propagated-inputs (list r-partykit))
    (home-page "https://cran.r-project.org/package=ATR")
    (synopsis "Alternative Tree Representation")
    (description
     "Plot party trees in left-right orientation instead of the classical top-down
layout.")
    (license license:gpl2)))

(define-public r-atpolr
  (package
    (name "r-atpolr")
    (version "0.1.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "atpolR" version))
              (sha256
               (base32
                "1mi2xghd5vxy6qx621dihx70wk3w1nqvm2h3j2drrb84b8zbvcvh"))))
    (properties `((upstream-name . "atpolR")))
    (build-system r-build-system)
    (propagated-inputs (list r-terra r-stringr r-sf r-rdpack))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/gsapijaszko/atpolR")
    (synopsis "ATPOL Grid Implementation")
    (description
     "ATPOL is a rectangular grid system used for botanical studies in Poland.  The
ATPOL grid was developed in Institute of Botany, Jagiellonian University,
Krakow, Poland in 70.  Since then it is widely used to represent distribution of
plants in Poland.  atpolR provides functions to translate geographic coordinates
to the grid and vice versa.  It also allows to create a choreograph map.")
    (license license:gpl3)))

(define-public r-atom4r
  (package
    (name "r-atom4r")
    (version "0.3-3")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "atom4R" version))
              (sha256
               (base32
                "08n9apmliwri1vyqwfvyqi7m8b9nj7zpi1vg8gcqlg17skxndm2m"))))
    (properties `((upstream-name . "atom4R")))
    (build-system r-build-system)
    (propagated-inputs (list r-zip
                             r-xml
                             r-readr
                             r-rdflib
                             r-r6
                             r-keyring
                             r-jsonlite
                             r-httr))
    (home-page "https://github.com/eblondel/atom4R")
    (synopsis "Tools to Handle and Publish Metadata as 'Atom' XML Format")
    (description
     "This package provides tools to read/write/publish metadata based on the Atom XML
syndication format.  This includes support of Dublin Core XML implementation,
and a client to API(s) implementing the AtomPub SWORD API specification.")
    (license license:expat)))

(define-public r-atnr
  (package
    (name "r-atnr")
    (version "1.0.2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ATNr" version))
              (sha256
               (base32
                "0p6pya91aklylig80xca68n5xx0ngzn8p0ba8sfrznqj53g8x4r5"))))
    (properties `((upstream-name . "ATNr")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpparmadillo r-rcpp r-desolve))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=ATNr")
    (synopsis "Run Allometric Trophic Networks Models")
    (description
     "This package implements the differential equations associated to different
versions of Allometric Trophic Models (ATN) to estimate the temporal dynamics of
species biomasses in food webs.  It offers several features to generate
synthetic food webs and to parametrise models as well as a wrapper to the ODE
solver deSolve.")
    (license license:gpl2+)))

(define-public r-atmopt
  (package
    (name "r-atmopt")
    (version "0.1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "atmopt" version))
              (sha256
               (base32
                "1h79ngq1236gz4w29fs3nj46a3m1x8a28z3xnhc6wn3a46cf8zzi"))))
    (properties `((upstream-name . "atmopt")))
    (build-system r-build-system)
    (propagated-inputs (list r-hiernet r-gtools r-doe-base))
    (home-page "https://cran.r-project.org/package=atmopt")
    (synopsis "Analysis-of-Marginal-Tail-Means")
    (description
     "This package provides functions for implementing the
Analysis-of-marginal-Tail-Means (ATM) method, a robust optimization method for
discrete black-box optimization.  Technical details can be found in Mak and Wu
(2018+) <arXiv:1712.03589>.  This work was supported by USARO grant
W911NF-17-1-0007.")
    (license license:gpl2+)))

(define-public r-atmchile
  (package
    (name "r-atmchile")
    (version "1.0.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AtmChile" version))
              (sha256
               (base32
                "0r8js8racs93vxbq62b44qj9m1vsp24dv81bmsg0a3smpk67zd46"))))
    (properties `((upstream-name . "AtmChile")))
    (build-system r-build-system)
    (propagated-inputs (list r-shinycssloaders
                             r-shiny
                             r-plotly
                             r-openair
                             r-lubridate
                             r-dt
                             r-data-table))
    (home-page "https://github.com/franciscoxaxo/AtmChile")
    (synopsis "Download Air Quality and Meteorological Information of Chile")
    (description
     "Download air quality and meteorological information of Chile from the National
Air Quality System (S.I.N.C.A.)<https://sinca.mma.gob.cl/> dependent on the
Ministry of the Environment and the Meteorological Directorate of Chile
(D.M.C.)<http://www.meteochile.gob.cl/> dependent on the Directorate General of
Civil Aeronautics.")
    (license license:gpl3)))

(define-public r-atlas
  (package
    (name "r-atlas")
    (version "1.0.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "atlas" version))
              (sha256
               (base32
                "02wm22j40llmdi6z3rzgbc5fpkzmjfq0xar33bypvj1dx1zxygnd"))))
    (properties `((upstream-name . "atlas")))
    (build-system r-build-system)
    (propagated-inputs (list r-testthat r-httr))
    (home-page "https://shahlab.stanford.edu/start")
    (synopsis "Stanford 'ATLAS' Search Engine API")
    (description
     "Stanford ATLAS (Advanced Temporal Search Engine) is a powerful tool that allows
constructing cohorts of patients extremely quickly and efficiently.  This
package is designed to interface directly with an instance of ATLAS search
engine and facilitates API queries and data dumps.  Prerequisite is a good
knowledge of the temporal language to be able to efficiently construct a query.
More information available at <https://shahlab.stanford.edu/start>.")
    (license license:gpl3)))

(define-public r-atime
  (package
    (name "r-atime")
    (version "2022.9.16")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "atime" version))
              (sha256
               (base32
                "07zmnbsglaaczn0sdzqz8749hsv578lr5w8qvjwl83sqpqmfs81y"))))
    (properties `((upstream-name . "atime")))
    (build-system r-build-system)
    (propagated-inputs (list r-lattice r-git2r r-data-table r-bench))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/tdhock/atime")
    (synopsis "Asymptotic Timing")
    (description
     "Computing and visualizing comparative asymptotic timings of different algorithms
and code versions.  Also includes functionality for comparing empirical timings
with expected references such as linear or quadratic,
<https://en.wikipedia.org/wiki/Asymptotic_computational_complexity> Also
includes functionality for measuring asymptotic memory and other quantities.")
    (license license:gpl3)))

(define-public r-atbounds
  (package
    (name "r-atbounds")
    (version "0.1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ATbounds" version))
              (sha256
               (base32
                "007gc9yjxwlhkb0mibxaa394xdiilfm8z6jbbqdn6wl986p07pg3"))))
    (properties `((upstream-name . "ATbounds")))
    (build-system r-build-system)
    (propagated-inputs (list r-mgcv))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/ATbounds/ATbounds-r/")
    (synopsis "Bounding Treatment Effects by Limited Information Pooling")
    (description
     "Estimation and inference methods for bounding average treatment effects (on the
treated) that are valid under an unconfoundedness assumption.  The bounds are
designed to be robust in challenging situations, for example, when the
conditioning variables take on a large number of different values in the
observed sample, or when the overlap condition is violated.  This robustness is
achieved by only using limited \"pooling\" of information across observations.
For more details, see the paper by Lee and Weidner (2021), \"Bounding Treatment
Effects by Pooling Limited Information across Observations,\" <arXiv:2111.05243>.")
    (license license:gpl3)))

(define-public r-atakrig
  (package
    (name "r-atakrig")
    (version "0.9.8")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "atakrig" version))
              (sha256
               (base32
                "14li2lpb2bksrfdhvnhs4k22jw4r4x9rm6lq9kn9hzif7gsibwr9"))))
    (properties `((upstream-name . "atakrig")))
    (build-system r-build-system)
    (propagated-inputs (list r-sp
                             r-snow
                             r-rgeos
                             r-rcpp
                             r-mass
                             r-gstat
                             r-foreach
                             r-fnn
                             r-dosnow))
    (home-page "https://cran.r-project.org/package=atakrig")
    (synopsis "Area-to-Area Kriging")
    (description
     "Point-scale variogram deconvolution from irregular/regular spatial support
according to Goovaerts, P., (2008) <doi: 10.1007/s11004-007-9129-1>; ordinary
area-to-area (co)Kriging and area-to-point (co)Kriging.")
    (license license:gpl2+)))

(define-public r-ataforecasting
  (package
    (name "r-ataforecasting")
    (version "0.0.57")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ATAforecasting" version))
              (sha256
               (base32
                "15ih8jmgp20iskgbn8v5gbbh3d724gmv0943lc09yvja7b6wxvba"))))
    (properties `((upstream-name . "ATAforecasting")))
    (build-system r-build-system)
    (propagated-inputs (list r-xts
                             r-tseries
                             r-tsa
                             r-timeseries
                             r-str
                             r-stlplus
                             r-seasonal
                             r-rdpack
                             r-rcpparmadillo
                             r-rcpp
                             r-forecast))
    (home-page "https://github.com/alsabtay/ATAforecasting")
    (synopsis
     "Automatic Time Series Analysis and Forecasting using the Ata Method")
    (description
     "The Ata method (Yapar et al. (2019) <doi:10.15672/hujms.461032>), an alternative
to exponential smoothing (described in Yapar (2016)
<doi:10.15672/HJMS.201614320580>, Yapar et al. (2017)
<doi:10.15672/HJMS.2017.493>), is a new univariate time series forecasting
method which provides innovative solutions to issues faced during the
initialization and optimization stages of existing forecasting methods.
Forecasting performance of the Ata method is superior to existing methods both
in terms of easy implementation and accurate forecasting.  It can be applied to
non-seasonal or seasonal time series which can be decomposed into four
components (remainder, level, trend and seasonal).  This methodology performed
well on the M3 and M4-competition data.  This package was written based on Ali
Sabri Taylan’s PhD dissertation.")
    (license license:gpl3+)))

(define-public r-atable
  (package
    (name "r-atable")
    (version "0.1.11")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "atable" version))
              (sha256
               (base32
                "0xna86l26f00n22hm3fn7kiqij87k6k7b5pa8jmld1bhw6j3cl4w"))))
    (properties `((upstream-name . "atable")))
    (build-system r-build-system)
    (propagated-inputs (list r-settings
                             r-reshape2
                             r-plyr
                             r-hmisc
                             r-effsize
                             r-doby
                             r-desctools))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/arminstroebel/atable")
    (synopsis "Create Tables for Reporting Clinical Trials")
    (description
     "Create Tables for Reporting Clinical Trials.  Calculates descriptive statistics
and hypothesis tests, arranges the results in a table ready for reporting with
LaTeX, HTML or Word.")
    (license license:gpl3)))

(define-public r-ata
  (package
    (name "r-ata")
    (version "1.1.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ata" version))
              (sha256
               (base32
                "08wcnfkbcq2al5ivdjkrjr8alaz0026992ra3ihyw6sd74mcracx"))))
    (properties `((upstream-name . "ata")))
    (build-system r-build-system)
    (propagated-inputs (list r-lpsolve))
    (home-page "https://cran.r-project.org/package=ata")
    (synopsis "Automated Test Assembly")
    (description
     "This package provides a collection of psychometric methods to process item
metadata and use target assessment and measurement blueprint constraints to
assemble a test form.  Currently two automatic test assembly (ata) approaches
are enabled.  For example, the weighted (positive) deviations method, wdm(),
proposed by Swanson and Stocking (1993) <doi:10.1177/014662169301700205> was
implemented in its full specification allowing for both item selection as well
as test form refinement.  The linear constraint programming approach, atalp(),
uses the linear equation solver by Berkelaar et.  al (2014)
<http://lpsolve.sourceforge.net/5.5/> to enable a variety of approaches to
select items.")
    (license license:lgpl2.0)))

(define-public r-asynchlong
  (package
    (name "r-asynchlong")
    (version "2.2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AsynchLong" version))
              (sha256
               (base32
                "0b6bx6r8cw0n7r9ynaadh3mdqyjlqizvklsb43af27iqqapl272d"))))
    (properties `((upstream-name . "AsynchLong")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=AsynchLong")
    (synopsis "Regression Analysis of Sparse Asynchronous Longitudinal Data")
    (description
     "Estimation of regression models for sparse asynchronous longitudinal
observations, where time-dependent response and covariates are mismatched and
observed intermittently within subjects.  Kernel weighted estimating equations
are used for generalized linear models with either time-invariant or
time-dependent coefficients.  Cao, H., Li, J., and Fine, J. P. (2016)
<doi:10.1214/16-EJS1141>.  Cao, H., Zeng, D., and Fine, J. P. (2015)
<doi:10.1111/rssb.12086>.")
    (license license:gpl2)))

(define-public r-async
  (package
    (name "r-async")
    (version "0.2.2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "async" version))
              (sha256
               (base32
                "1m12hhqxmvj0nyfwbjq66kb435c38flqgbn0gqlfzi6lpmiapnpj"))))
    (properties `((upstream-name . "async")))
    (build-system r-build-system)
    (propagated-inputs (list r-promises r-nseval r-later r-itertools
                             r-iterators))
    (native-inputs (list r-knitr))
    (home-page "https://crowding.github.io/async/")
    (synopsis "Asynchronous Code Constructs: Generators, Yield, Async, Await")
    (description
     "Write sequential-looking code that pauses and resumes.  gen() creates a
generator, an iterator that returns a value and pauses each time it reaches a
yield() call.  async() creates a promise, which runs until it reaches a call to
await(), then resumes when information is available.  These work similarly to
generator and async constructs from Python or JavaScript'.  Objects produced are
compatible with the iterators and promises packages.")
    (license license:gpl2)))

(define-public r-asymptor
  (package
    (name "r-asymptor")
    (version "1.1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "asymptor" version))
              (sha256
               (base32
                "0g8z0nqjp4a9lxvdmzhyx1sqvdrkd9vd0b3i3qjbm4a542jf0aga"))))
    (properties `((upstream-name . "asymptor")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://hugogruson.fr/asymptor/")
    (synopsis "Estimate Asymptomatic Cases via Capture/Recapture Methods")
    (description
     "Estimate the lower and upper bound of asymptomatic cases in an epidemic using
the capture/recapture methods from Böhning et al. (2020)
<doi:10.1016/j.ijid.2020.06.009> and Rocchetti et al. (2020)
<doi:10.1101/2020.07.14.20153445>.  Note there is currently some discussion
about the validity of the methods implemented in this package.  You should read
carefully the original articles, alongside this answer from Li et al. (2022)
<doi:10.48550/arXiv.2209.11334> before using this package in your project.")
    (license license:gpl3)))

(define-public r-asymptest
  (package
    (name "r-asymptest")
    (version "0.1.4")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "asympTest" version))
              (sha256
               (base32
                "02l07psiy1888zx86j2r1l5lznz47wdmzbh39pd2nbj8r9i80szr"))))
    (properties `((upstream-name . "asympTest")))
    (build-system r-build-system)
    (home-page "https://www.r-project.org")
    (synopsis
     "Simple R Package for Classical Parametric Statistical Tests and Confidence Intervals in Large Samples")
    (description
     "One and two sample mean and variance tests (differences and ratios) are
considered.  The test statistics are all expressed in the same form as the
Student t-test, which facilitates their presentation in the classroom.  This
contribution also fills the gap of a robust (to non-normality) alternative to
the chi-square single variance test for large samples, since no such procedure
is implemented in standard statistical software.")
    (license license:gpl2+)))

(define-public r-asymmetry-measures
  (package
    (name "r-asymmetry-measures")
    (version "0.2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "asymmetry.measures" version))
              (sha256
               (base32
                "039afqmdir200aijln9q0g3rkahkxqahw6yz5mnw62jsslr9xskb"))))
    (properties `((upstream-name . "asymmetry.measures")))
    (build-system r-build-system)
    (propagated-inputs (list r-sn r-skewt r-gamlss-dist))
    (home-page "https://cran.r-project.org/package=asymmetry.measures")
    (synopsis "Asymmetry Measures for Probability Density Functions")
    (description
     "This package provides functions and examples for the weak and strong density
asymmetry measures in the articles: \"A measure of asymmetry\", Patil, Patil and
Bagkavos (2012) <doi:10.1007/s00362-011-0401-6> and \"A measure of asymmetry
based on a new necessary and sufficient condition for symmetry\", Patil, Bagkavos
and Wood (2014) <doi:10.1007/s13171-013-0034-z>.  The measures provided here are
useful for quantifying the asymmetry of the shape of a density of a random
variable.  The package facilitates implementation of the measures which are
applicable in a variety of fields including e.g. probability theory, statistics
and economics.")
    (license license:gpl2+)))

(define-public r-asymmetry
  (package
    (name "r-asymmetry")
    (version "2.0.4")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "asymmetry" version))
              (sha256
               (base32
                "1zppf4gb0rz9c4ixd6fym2qyjs8ddzq09is1rlf000mcnarfl22b"))))
    (properties `((upstream-name . "asymmetry")))
    (build-system r-build-system)
    (propagated-inputs (list r-smacof r-gplots))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=asymmetry")
    (synopsis "Multidimensional Scaling of Asymmetric Proximities")
    (description
     "Multidimensional scaling models and methods for the visualization and analysis
of asymmetric proximity data <doi:10.1111/j.2044-8317.1996.tb01078.x>.  An
asymmetric data matrix has the same number of rows and columns, and these rows
and columns refer to the same set of objects.  At least some elements in the
upper-triangle are different from the corresponding elements in the lower
triangle.  An example of an asymmetric matrix is a student migration table,
where the rows correspond to the countries of origin of the students and the
columns to the destination countries.  This package provides algorithms for
three multidimensional scaling models.  These are the slide-vector model
<doi:10.1007/BF02294474>, a scaling model with unique dimensions and the
asymscal model for asymmetric multidimensional scaling.  Furthermore, a heat map
for skew-symmetric data, and the decomposition of asymmetry are provided for the
exploratory analysis of asymmetric tables.")
    (license license:gpl3+)))

(define-public r-asymmetricsords
  (package
    (name "r-asymmetricsords")
    (version "1.0.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AsymmetricSORDs" version))
              (sha256
               (base32
                "0a6ika2vlnklbsr7lmihysbhzzc5za2aw77iw6pc19cw6mba6mpy"))))
    (properties `((upstream-name . "AsymmetricSORDs")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=AsymmetricSORDs")
    (synopsis "Asymmetric Second Order Rotatable Designs (AsymmetricSORDs)")
    (description
     "Response surface designs (RSDs) are widely used for Response Surface Methodology
(RSM) based optimization studies, which aid in exploring the relationship
between a group of explanatory variables and one or more response variable(s)
(G.E.P. Box and K.B. Wilson (1951), \"On the experimental attainment of optimum
conditions\" ; M. Hemavathi, Shashi Shekhar, Eldho Varghese, Seema Jaggi, Bikas
Sinha & Nripes Kumar Mandal (2022) <DOI:
10.1080/03610926.2021.1944213>.\"Theoretical developments in response surface
designs: an informative review and further thoughts\".).  Second order rotatable
designs are the most prominent and popular class of designs used for process and
product optimization trials but it is suitable for situations when all the
number of levels for each factor is the same.  In many practical situations,
RSDs with asymmetric levels (J.S. Mehta and M.N. Das (1968). \"Asymmetric
rotatable designs and orthogonal transformations\" ; M. Hemavathi, Eldho
Varghese, Shashi Shekhar & Seema Jaggi (2020) <DOI:
10.1080/02664763.2020.1864817>. \"Sequential asymmetric third order rotatable
designs (SATORDs)\" .) are more suitable as these designs explore more regions in
the design space.This package contains functions named Asords() ,CCD_coded(),
CCD_original(), SORD_coded() and SORD_original() for generating
asymmetric/symmetric RSDs along with the randomized layout.  It also contains
another function named Pred.var() for generating the variance of predicted
response as well as the moment matrix based on a second order model.")
    (license license:gpl2+)))

(define-public r-asymld
  (package
    (name "r-asymld")
    (version "0.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "asymLD" version))
              (sha256
               (base32
                "1q05pxwn6arpalspgf2m0cym4ivnwyv94i58k9kaihd37kvm5lgc"))))
    (properties `((upstream-name . "asymLD")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=asymLD")
    (synopsis
     "Asymmetric Linkage Disequilibrium (ALD) for Polymorphic Genetic Data")
    (description
     "Computes asymmetric LD measures (ALD) for multi-allelic genetic data.  These
measures are identical to the correlation measure (r) for bi-allelic data.")
    (license license:gpl2)))

(define-public r-asylum
  (package
    (name "r-asylum")
    (version "1.0.2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "asylum" version))
              (sha256
               (base32
                "1vasdbg4blsgd9976ivzj0r97zwsna4rxj7c9d4xlnmvs4rmb57j"))))
    (properties `((upstream-name . "asylum")))
    (build-system r-build-system)
    (home-page "https://github.com/britishredcrosssociety/asylum")
    (synopsis "Data on Asylum and Resettlement for the UK")
    (description
     "Data on Asylum and Resettlement for the UK, provided by the Home Office
<https://www.gov.uk/government/statistics/immigration-statistics-year-ending-june-2022>.")
    (license license:expat)))

(define-public r-asyk
  (package
    (name "r-asyk")
    (version "1.5.5")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AsyK" version))
              (sha256
               (base32
                "0mr09gfxq2xsdrh7h28fkczhs44m367gf7zj09kc5lc5zwd9fs83"))))
    (properties `((upstream-name . "AsyK")))
    (build-system r-build-system)
    (propagated-inputs (list r-deltd))
    (home-page "https://CRAN.R-project.org/package=AsyK")
    (synopsis "Kernel Density Estimation")
    (description
     "This package provides a collection of functions related to density estimation by
using Chen's (2000) idea.  Mean Squared Errors (MSE) are calculated for
estimated curves.  For this purpose, R functions allow the distribution to be
Gamma, Exponential or Weibull.  For details see Chen (2000), Scaillet (2004)
<doi:10.1080/10485250310001624819> and Khan and Akbar.")
    (license license:gpl2)))

(define-public r-asv
  (package
    (name "r-asv")
    (version "1.1.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ASV" version))
              (sha256
               (base32
                "1cwsfc5mylivg65mb93d0v8kalirq5vwjx78fjyylsdc4w33gzqb"))))
    (properties `((upstream-name . "ASV")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcppprogress r-rcpparmadillo r-rcpp r-freqdom))
    (home-page
     "https://sites.google.com/view/omori-stat/english/software/asv-r")
    (synopsis "Stochastic Volatility Models with or without Leverage")
    (description
     "The efficient Markov chain Monte Carlo estimation of stochastic volatility
models with and without leverage (asymmetric and symmetric stochastic volatility
models).  Further, it computes the logarithm of the likelihood given parameters
using particle filters.")
    (license license:gpl2+)))

(define-public r-astrofns
  (package
    (name "r-astrofns")
    (version "4.2-1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "astroFns" version))
              (sha256
               (base32
                "0c81q9xddd9m2lhbv7r2aq1w262vjamcv8qg4mgrndww8n6vf8zn"))))
    (properties `((upstream-name . "astroFns")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=astroFns")
    (synopsis "Astronomy: Time and Position Functions, Misc. Utilities")
    (description "Miscellaneous astronomy functions, utilities, and data.")
    (license license:gpl2+)))

(define-public r-astrodatr
  (package
    (name "r-astrodatr")
    (version "0.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "astrodatR" version))
              (sha256
               (base32
                "00689px4znwmlp6qbj6z2a51b7ylx1yrrjpv6zjkvrwpv6lyj9fw"))))
    (properties `((upstream-name . "astrodatR")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=astrodatR")
    (synopsis "Astronomical Data")
    (description
     "This package provides a collection of 19 datasets from contemporary astronomical
research.  They are described the textbook `Modern Statistical Methods for
Astronomy with R Applications by Eric D. Feigelson and G. Jogesh Babu (Cambridge
University Press, 2012, Appendix C) or on the website of Penn State's Center for
Astrostatistics (http://astrostatistics.psu.edu/datasets).  These datasets can
be used to exercise methodology involving: density estimation; heteroscedastic
measurement errors; contingency tables; two-sample hypothesis tests; spatial
point processes; nonlinear regression; mixture models; censoring and truncation;
multivariate analysis; classification and clustering; inhomogeneous Poisson
processes; periodic and stochastic time series analysis.")
    (license (list license:gpl2+ license:gpl3+))))

(define-public r-astrochron
  (package
    (name "r-astrochron")
    (version "1.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "astrochron" version))
              (sha256
               (base32
                "0gvdilsacgbdcwz8598psxan3q5im5iw6xrn9zbdbg7sswrvc5ff"))))
    (properties `((upstream-name . "astrochron")))
    (build-system r-build-system)
    (propagated-inputs (list r-viridislite
                             r-multitaper
                             r-iterators
                             r-idpmisc
                             r-foreach
                             r-fields
                             r-doparallel))
    (native-inputs (list gfortran))
    (home-page "https://cran.r-project.org/package=astrochron")
    (synopsis "Computational Tool for Astrochronology")
    (description
     "Routines for astrochronologic testing, astronomical time scale construction, and
time series analysis <doi:10.1016/j.earscirev.2018.11.015>.  Also included are a
range of statistical analysis and modeling routines that are relevant to time
scale development and paleoclimate analysis.")
    (license license:gpl3)))

(define-public r-asthmanhanes
  (package
    (name "r-asthmanhanes")
    (version "1.1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AsthmaNHANES" version))
              (sha256
               (base32
                "106c6fh20s98fzixs4jpa4d413himrfg31rzwsxp72yldqxg70fx"))))
    (properties `((upstream-name . "AsthmaNHANES")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=AsthmaNHANES")
    (synopsis "Asthma Data Sets from NHANES")
    (description
     "Data sets and examples from National Health and Nutritional Examination Survey
(NHANES).")
    (license license:gpl3)))

(define-public r-asterisk
  (package
    (name "r-asterisk")
    (version "1.4.2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "asteRisk" version))
              (sha256
               (base32
                "1yk31gccab4i5v1wy954f3hqkdi58s224njiqkw3k4kib6xdasnj"))))
    (properties `((upstream-name . "asteRisk")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcppparallel r-rcpp r-onion r-nanotime
                             r-desolve))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=asteRisk")
    (synopsis "Computation of Satellite Position")
    (description
     "This package provides basic functionalities to calculate the position of
satellites given a known state vector.  The package includes implementations of
the SGP4 and SDP4 simplified perturbation models to propagate orbital state
vectors, as well as utilities to read TLE files and convert coordinates between
different frames of reference.  Several of the functionalities of the package
(including the high-precision numerical orbit propagator) require the
coefficients and data included in the asteRiskData package, available in a drat
repository.  To install this data package, run install.packages(\"asteRiskData\",
repos=\"https://rafael-ayala.github.io/drat/\")'.  Felix R. Hoots, Ronald L.
Roehrich and T.S. Kelso (1988)
<https://celestrak.org/NORAD/documentation/spacetrk.pdf>.  David Vallado, Paul
Crawford, Richard Hujsak and T.S. Kelso (2012) <doi:10.2514/6.2006-6753>.  Felix
R. Hoots, Paul W. Schumacher Jr.  and Robert A. Glover (2014)
<doi:10.2514/1.9161>.")
    (license license:gpl3)))

(define-public r-aster2
  (package
    (name "r-aster2")
    (version "0.3")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "aster2" version))
              (sha256
               (base32
                "17d200sg0vn1fj6lb480dhszm70q6ipjldilb3x0jp72hiczakk9"))))
    (properties `((upstream-name . "aster2")))
    (build-system r-build-system)
    (propagated-inputs (list r-matrix))
    (home-page "http://www.stat.umn.edu/geyer/aster/")
    (synopsis "Aster Models")
    (description
     "Aster models are exponential family regression models for life history analysis.
 They are like generalized linear models except that elements of the response
vector can have different families (e.  g., some Bernoulli, some Poisson, some
zero-truncated Poisson, some normal) and can be dependent, the dependence
indicated by a graphical structure.  Discrete time survival analysis,
zero-inflated Poisson regression, and generalized linear models that are
exponential family (e.  g., logistic regression and Poisson regression with log
link) are special cases.  Main use is for data in which there is survival over
discrete time periods and there is additional data about what happens
conditional on survival (e.  g., number of offspring).  Uses the exponential
family canonical parameterization (aster transform of usual parameterization).
Unlike the aster package, this package does dependence groups (nodes of the
graph need not be conditionally independent given their predecessor node),
including multinomial and two-parameter normal as families.  Thus this package
also generalizes mark-capture-recapture analysis.")
    (license license:gpl2+)))

(define-public r-aster
  (package
    (name "r-aster")
    (version "1.1-2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "aster" version))
              (sha256
               (base32
                "0vf1ffkn4a3bz2lgz1gn2hjgp8c2v9ch05d5r1gh2q77zijvry1m"))))
    (properties `((upstream-name . "aster")))
    (build-system r-build-system)
    (propagated-inputs (list r-trust))
    (home-page "http://www.stat.umn.edu/geyer/aster/")
    (synopsis "Aster Models")
    (description
     "Aster models (Geyer, Wagenius, and Shaw, 2007, <doi:10.1093/biomet/asm030>;
Shaw, Geyer, Wagenius, Hangelbroek, and Etterson, 2008, <doi:10.1086/588063>;
Geyer, Ridley, Latta, Etterson, and Shaw, 2013, <doi:10.1214/13-AOAS653>) are
exponential family regression models for life history analysis.  They are like
generalized linear models except that elements of the response vector can have
different families (e.  g., some Bernoulli, some Poisson, some zero-truncated
Poisson, some normal) and can be dependent, the dependence indicated by a
graphical structure.  Discrete time survival analysis, life table analysis,
zero-inflated Poisson regression, and generalized linear models that are
exponential family (e.  g., logistic regression and Poisson regression with log
link) are special cases.  Main use is for data in which there is survival over
discrete time periods and there is additional data about what happens
conditional on survival (e.  g., number of offspring).  Uses the exponential
family canonical parameterization (aster transform of usual parameterization).
There are also random effects versions of these models.")
    (license license:expat)))

(define-public r-ast2ast
  (package
    (name "r-ast2ast")
    (version "0.2.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ast2ast" version))
              (sha256
               (base32
                "1dw204l1lq6jlv6rzd6amjbf1vz6vhk6cb0qdjls4254cg01gs3p"))))
    (properties `((upstream-name . "ast2ast")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpparmadillo r-rcpp r-r6 r-purrr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/Konrad1991/ast2ast")
    (synopsis "Translates an R Function to a C++ Function")
    (description
     "Enable translation of a tiny subset of R to C++.  The user has to define a R
function which gets translated.  For a full list of possible functions check the
documentation.  After translation an R function is returned which is a shallow
wrapper around the C++ code.  Alternatively an external pointer to the C++
function is returned to the user.  The intention of the package is to generate
fast functions which can be used as ode-system or during optimization.")
    (license license:gpl2)))

(define-public r-ast
  (package
    (name "r-ast")
    (version "0.1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AST" version))
              (sha256
               (base32
                "0z5dw5qw0i61v4796ms7pp66f9y4ylxrcls31ixzcmkklh3rcnp3"))))
    (properties `((upstream-name . "AST")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=AST")
    (synopsis "Age-Spatial-Temporal Model")
    (description
     "Fits a model to adjust and consider additional variations in three dimensions of
age groups, time, and space on residuals excluded from a prediction model that
have residual such as: linear regression, mixed model and so on.  Details are
given in Foreman et al. (2015) <doi:10.1186/1478-7954-10-1>.")
    (license (list license:gpl2 license:gpl3))))

(define-public r-assortnet
  (package
    (name "r-assortnet")
    (version "0.12")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "assortnet" version))
              (sha256
               (base32
                "1vyzrb8vsi9pcdn6jd83k77bg0q2a3dwdvlnmxnshqiif2pakb8m"))))
    (properties `((upstream-name . "assortnet")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=assortnet")
    (synopsis
     "Calculate the Assortativity Coefficient of Weighted and Binary Networks")
    (description
     "This package provides functions to calculate the assortment of vertices in
social networks.  This can be measured on both weighted and binary networks,
with discrete or continuous vertex values.")
    (license license:gpl2)))

(define-public r-assoctests
  (package
    (name "r-assoctests")
    (version "1.0-1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AssocTests" version))
              (sha256
               (base32
                "1wp5swnpd6m5g4zm14lllclmw058513n1g3kq1iqc0acjavkqy17"))))
    (properties `((upstream-name . "AssocTests")))
    (build-system r-build-system)
    (propagated-inputs (list r-mvtnorm r-fextremes r-combinat r-cluster))
    (home-page "https://cran.r-project.org/package=AssocTests")
    (synopsis "Genetic Association Studies")
    (description
     "Some procedures including EIGENSTRAT (a procedure for detecting and correcting
for population stratification through searching for the eigenvectors in genetic
association studies), PCoC (a procedure for correcting for population
stratification through calculating the principal coordinates and the clustering
of the subjects), Tracy-Widom test (a procedure for detecting the significant
eigenvalues of a matrix), distance regression (a procedure for detecting the
association between a distance matrix and some independent variants of
interest), single-marker test (a procedure for identifying the association
between the genotype at a biallelic marker and a trait using the Wald test or
the Fisher's exact test), MAX3 (a procedure for testing for the association
between a single nucleotide polymorphism and a binary phenotype using the
maximum value of the three test statistics derived for the recessive, additive,
and dominant models), nonparametric trend test (a procedure for testing for the
association between a genetic variant and a non-normal distributed quantitative
trait based on the nonparametric risk), and nonparametric MAX3 (a procedure for
testing for the association between a biallelic single nucleotide polymorphism
and a quantitative trait using the maximum value of the three nonparametric
trend tests derived for the recessive, additive, and dominant models), which are
commonly used in genetic association studies.  To cite this package in
publications use: Lin Wang, Wei Zhang, and Qizhai Li.  AssocTests: An R Package
for Genetic Association Studies.  Journal of Statistical Software.  2020; 94(5):
1-26.")
    (license license:gpl2)))

(define-public r-assocind
  (package
    (name "r-assocind")
    (version "1.0.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "assocInd" version))
              (sha256
               (base32
                "16yzgvlqbapjhvzm5nw8vfrhh8mp9llnhck4bpgmszyrh93z1ha5"))))
    (properties `((upstream-name . "assocInd")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=assocInd")
    (synopsis
     "Implements New and Existing Association Indices for Constructing Animal Social Networks")
    (description
     "This package implements several new association indices that can control for
various types of errors.  Also includes existing association indices and
functions for simulating the effects of different rates of error on estimates of
association strength between individuals using each method.")
    (license license:gpl2)))

(define-public r-assocafc
  (package
    (name "r-assocafc")
    (version "1.0.2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AssocAFC" version))
              (sha256
               (base32
                "1rjiiir472dnr15xyvpn81s62nf01gl70khr8mrni65ssp5m30fb"))))
    (properties `((upstream-name . "AssocAFC")))
    (build-system r-build-system)
    (propagated-inputs (list r-compquadform))
    (home-page "https://www.r-project.org")
    (synopsis "Allele Frequency Comparison")
    (description
     "When doing association analysis one does not always have the genotypes for the
control population.  In such cases it may be necessary to fall back on frequency
based tests using well known sources for the frequencies in the control
population, for instance, from the 1000 Genomes Project.  The Allele Frequency
Comparison ('AssocAFC') package performs multiple rare variant association
analyses in both population and family-based GWAS (Genome-Wide Association
Study) designs.  It includes three score tests that are based on the difference
of the sum of allele frequencies between cases and controls.  Two of these
tests, Wcorrected() and Wqls(), are collapsing-based tests and suffer from
having protective and risk variants.  The third test, afcSKAT(), is a score test
that overcomes the mix of SNP (Single-Nucleotide Polymorphism) effect
directions.  For more details see Saad M and Wijsman EM (2017)
<doi:10.1093/bib/bbx107>.")
    (license license:gpl3+)))

(define-public r-assistant
  (package
    (name "r-assistant")
    (version "1.4.3")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ASSISTant" version))
              (sha256
               (base32
                "0apaj4lfkbg08xrw8mknf50s1vyd4j5mbwciwgblq7ydh3pyjxaj"))))
    (properties `((upstream-name . "ASSISTant")))
    (build-system r-build-system)
    (propagated-inputs (list r-r6 r-mvtnorm r-magrittr r-knitr r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/bnaras/ASSISTant")
    (synopsis "Adaptive Subgroup Selection in Group Sequential Trials")
    (description
     "Clinical trial design for subgroup selection in three-stage group sequential
trial as described in Lai, Lavori and Liao (2014,
<doi:10.1016/j.cct.2014.09.001>).  Includes facilities for design, exploration
and analysis of such trials.  An implementation of the initial DEFUSE-3 trial is
also provided as a vignette.")
    (license license:gpl2+)))

(define-public r-assist
  (package
    (name "r-assist")
    (version "3.1.8")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "assist" version))
              (sha256
               (base32
                "1ayr3mvv31dm3ff1jfwfshhrfhpyvqnshw3azp0pz96d1f9f31hj"))))
    (properties `((upstream-name . "assist")))
    (build-system r-build-system)
    (propagated-inputs (list r-nlme r-lattice))
    (native-inputs (list gfortran))
    (home-page "https://yuedong.faculty.pstat.ucsb.edu/software.html")
    (synopsis "Suite of R Functions Implementing Spline Smoothing Techniques")
    (description
     "Fit various smoothing spline models.  Includes an ssr() function for smoothing
spline regression, an nnr() function for nonparametric nonlinear regression, an
snr() function for semiparametric nonlinear regression, an slm() function for
semiparametric linear mixed-effects models, and an snm() function for
semiparametric nonlinear mixed-effects models.  See Wang (2011)
<doi:10.1201/b10954> for an overview.")
    (license license:gpl2)))

(define-public r-assignr
  (package
    (name "r-assignr")
    (version "2.2.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "assignR" version))
              (sha256
               (base32
                "1v9vc5klyk713xp1xhcndfq0qprh0553a6wr9yb6c5p5r7mwgrlh"))))
    (properties `((upstream-name . "assignR")))
    (build-system r-build-system)
    (propagated-inputs (list r-sp
                             r-rlang
                             r-rgdal
                             r-raster
                             r-mvnfast
                             r-maptools
                             r-geosphere))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=assignR")
    (synopsis "Infer Geographic Origin from Isotopic Data")
    (description
     "Routines for re-scaling isotope maps using known-origin tissue isotope data,
assigning origin of unknown samples, and summarizing and assessing assignment
results.  Methods are adapted from Wunder (2010, in ISBN:9789048133536) and
Vander Zanden, H. B. et al. (2014) <doi:10.1111/2041-210X.12229> as described in
Ma, C. et al. (2020) <doi:10.1111/2041-210X.13426>.")
    (license license:gpl3)))

(define-public r-assignpop
  (package
    (name "r-assignpop")
    (version "1.2.4")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "assignPOP" version))
              (sha256
               (base32
                "1zzapgzf09l39bckwykzr8im2wxmndpmzykll2wi7njwlklpjry3"))))
    (properties `((upstream-name . "assignPOP")))
    (build-system r-build-system)
    (propagated-inputs (list r-tree
                             r-stringr
                             r-reshape2
                             r-randomforest
                             r-mass
                             r-ggplot2
                             r-foreach
                             r-e1071
                             r-doparallel
                             r-caret))
    (home-page "https://github.com/alexkychen/assignPOP")
    (synopsis
     "Population Assignment using Genetic, Non-Genetic or Integrated Data in a Machine Learning Framework")
    (description
     "Use Monte-Carlo and K-fold cross-validation coupled with machine- learning
classification algorithms to perform population assignment, with functionalities
of evaluating discriminatory power of independent training samples, identifying
informative loci, reducing data dimensionality for genomic data, integrating
genetic and non-genetic data, and visualizing results.")
    (license license:gpl2+)))

(define-public r-assetpricing
  (package
    (name "r-assetpricing")
    (version "1.0-3")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AssetPricing" version))
              (sha256
               (base32
                "199ygwfddpzxnj388gxkn7xyhnvjr24f5jg4lnydh0z7pb96pm5r"))))
    (properties `((upstream-name . "AssetPricing")))
    (build-system r-build-system)
    (propagated-inputs (list r-polynom r-desolve))
    (home-page "http://www.stat.auckland.ac.nz/~rolf/")
    (synopsis "Optimal Pricing of Assets with Fixed Expiry Date")
    (description
     "Calculates the optimal price of assets (such as airline flight seats, hotel room
bookings) whose value becomes zero after a fixed ``expiry date''.  Assumes
potential customers arrive (possibly in groups) according to a known
inhomogeneous Poisson process.  Also assumes a known time-varying elasticity of
demand (price sensitivity) function.  Uses elementary techniques based on
ordinary differential equations.  Uses the package deSolve to effect the
solution of these differential equations.")
    (license license:gpl2+)))

(define-public r-assetcorr
  (package
    (name "r-assetcorr")
    (version "1.0.4")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AssetCorr" version))
              (sha256
               (base32
                "0r98li2lxhfap1hn6h0l78phpm9m1nlcqhwzpq0ahhw0b1rd4qkf"))))
    (properties `((upstream-name . "AssetCorr")))
    (build-system r-build-system)
    (propagated-inputs (list r-vinecopula
                             r-rdpack
                             r-qpdf
                             r-numderiv
                             r-mvtnorm
                             r-mvquad
                             r-knitr
                             r-ggplot2
                             r-boot))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=AssetCorr")
    (synopsis "Estimating Asset Correlations from Default Data")
    (description
     "This package provides functions for the estimation of intra- and inter-cohort
correlations in the Vasicek credit portfolio model.  For intra-cohort
correlations, the package covers the two method of moments estimators of Gordy
(2000) <doi:10.1016/S0378-4266(99)00054-0>, the method of moments estimator of
Lucas (1995) <https://jfi.pm-research.com/content/4/4/76> and a Binomial
approximation extension of this approach.  Moreover, the maximum likelihood
estimators of Gordy and Heitfield (2010)
<http://elsa.berkeley.edu/~mcfadden/e242_f03/heitfield.pdf> and Duellmann and
Gehde-Trapp (2004) <http://hdl.handle.net/10419/19729> are implemented.  For
inter-cohort correlations, the method of moments estimator of Bluhm and Overbeck
(2003) <doi:10.1007/978-3-642-59365-9_2>/Bams et al. (2016)
<https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2676595> is provided and
the maximum likelihood estimators comprise the approaches of Gordy and Heitfield
(2010)/Kalkbrener and Onwunta (2010) <ISBN: 978-1906348250> and Pfeuffer et al.
(2020).  Bootstrap and Jackknife procedures for bias correction are included as
well as the method of moments estimator of Frei and Wunsch (2018)
<doi:10.21314/JCR.2017.231> for auto-correlated time series.")
    (license license:gpl3)))

(define-public r-assetallocation
  (package
    (name "r-assetallocation")
    (version "1.0.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AssetAllocation" version))
              (sha256
               (base32
                "02r9a21696y1gj5qw01jddnyda6hm962l1am7igrqyywh05canch"))))
    (properties `((upstream-name . "AssetAllocation")))
    (build-system r-build-system)
    (propagated-inputs (list r-zoo
                             r-xts
                             r-riskportfolios
                             r-riskparityportfolio
                             r-quantmod
                             r-performanceanalytics
                             r-nmof))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/rubetron/AssetAllocation")
    (synopsis "Backtesting Simple Asset Allocation Strategies")
    (description
     "Easy and quick testing of customizable asset allocation strategies.  Users can
rely on their own data, or have the package automatically download data from
Yahoo Finance (<https://finance.yahoo.com/>).  Several pre-loaded portfolios
with data are available, including some which are discussed in Faber (2015,
ISBN:9780988679924).")
    (license license:gpl3+)))

(define-public r-assert
  (package
    (name "r-assert")
    (version "1.0.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "assert" version))
              (sha256
               (base32
                "0n5l48yb0djl6rdj50p1dslpw3c5kbi15yz6z6rdgic575gjwzdc"))))
    (properties `((upstream-name . "assert")))
    (build-system r-build-system)
    (home-page "https://github.com/OlivierBinette/assert")
    (synopsis "Validate Function Arguments")
    (description
     "Lightweight validation tool for checking function arguments and validating data
analysis scripts.  This is an alternative to stopifnot() from the base package
and to assert_that() from the assertthat package.  It provides more informative
error messages and facilitates debugging.")
    (license license:gpl2+)))

(define-public r-assa
  (package
    (name "r-assa")
    (version "2.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ASSA" version))
              (sha256
               (base32
                "10r5406g6i0959k1zm5h9cbwqmnyf7zy80ahiqsyrapm3g5rphxg"))))
    (properties `((upstream-name . "ASSA")))
    (build-system r-build-system)
    (native-inputs (list gfortran))
    (home-page "https://cran.r-project.org/package=ASSA")
    (synopsis "Applied Singular Spectrum Analysis (ASSA)")
    (description
     "This package provides functions to model and decompose time series into
principal components using singular spectrum analysis (de Carvalho and Rua
(2017) <doi:10.1016/j.ijforecast.2015.09.004>; de Carvalho et al (2012)
<doi:10.1016/j.econlet.2011.09.007>).")
    (license license:gpl3+)))

(define-public r-asrgenomics
  (package
    (name "r-asrgenomics")
    (version "1.1.3")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ASRgenomics" version))
              (sha256
               (base32
                "1yl3q1fjfyl0v0wpbgnbh8zj5j8zi1imf19cj66fdvji3i4c4lsi"))))
    (properties `((upstream-name . "ASRgenomics")))
    (build-system r-build-system)
    (propagated-inputs (list r-superheat
                             r-scattermore
                             r-matrix
                             r-ggplot2
                             r-factoextra
                             r-ellipse
                             r-data-table
                             r-crayon
                             r-cowplot
                             r-aghmatrix))
    (home-page "https://cran.r-project.org/package=ASRgenomics")
    (synopsis "'ASReml-R' Genomics Tools")
    (description
     "Presents a series of molecular and genetic routines in the R environment with
the aim of assisting in analytical pipelines before and after the use of asreml
or another library to perform analyses such as Genomic Selection or Genome-Wide
Association Analyses.  Methods and examples are described in Gezan, Oliveira,
Galli, and Murray (2022)
<https://asreml.kb.vsni.co.uk/wp-content/uploads/sites/3/ASRgenomics_Manual.pdf>.")
    (license license:expat)))

(define-public r-asremlplus
  (package
    (name "r-asremlplus")
    (version "4.3.40")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "asremlPlus" version))
              (sha256
               (base32
                "03w16mlri6mb4zigb9fj8rfz10kwwwdkqf4l9x8az5z52aq7b7zc"))))
    (properties `((upstream-name . "asremlPlus")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr
                             r-sticky
                             r-reshape2
                             r-rcolorbrewer
                             r-ggplot2
                             r-foreach
                             r-dplyr
                             r-doparallel
                             r-dae))
    (home-page "http://chris.brien.name")
    (synopsis
     "Augments 'ASReml-R' in Fitting Mixed Models and Packages Generally in Exploring Prediction Differences")
    (description
     "Assists in automating the selection of terms to include in mixed models when
asreml is used to fit the models.  Also used to display, in tables and graphs,
predictions obtained using any model fitting function and to explore differences
between predictions.  The content falls into the following natural groupings:
(i) Data, (ii) Object manipulation functions, (iii) Model modification
functions, (iv) Model testing functions, (v) Model diagnostics functions, (vi)
Prediction production and presentation functions, (vii) Response transformation
functions, and (viii) Miscellaneous functions (for further details see
asremlPlus-package in help).  A history of the fitting of a sequence of models
is kept in a data frame.  Procedures are available for choosing models that
conform to the hierarchy or marginality principle and for displaying predictions
for significant terms in tables and graphs.  The asreml package provides a
computationally efficient algorithm for fitting mixed models using Residual
Maximum Likelihood.  It is a commercial package that can be purchased from VSNi
<https://vsni.co.uk/> as asreml-R', who will supply a zip file for local
installation/updating (see <https://asreml.kb.vsni.co.uk/>).  It is not needed
for functions that are methods for alldiffs and data.frame objects.  The package
asremPlus can also be installed from <http://chris.brien.name/rpackages/>.")
    (license license:expat)))

(define-public r-aspu
  (package
    (name "r-aspu")
    (version "1.50")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "aSPU" version))
              (sha256
               (base32
                "0rh21dj5913nxhdndqfhxvm6mvwnacraf7l3bac09awm7cfhk511"))))
    (properties `((upstream-name . "aSPU")))
    (build-system r-build-system)
    (propagated-inputs (list r-mvtnorm r-matrixstats r-mass r-gee r-fields))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/ikwak2/aSPU")
    (synopsis "Adaptive Sum of Powered Score Test")
    (description
     "R codes for the (adaptive) Sum of Powered Score ('SPU and aSPU') tests, inverse
variance weighted Sum of Powered score ('SPUw and aSPUw') tests and gene-based
and some pathway based association tests (Pathway based Sum of Powered Score
tests ('SPUpath'), adaptive SPUpath ('aSPUpath') test, GEEaSPU test for multiple
traits - single SNP (single nucleotide polymorphism) association in generalized
estimation equations, MTaSPUs test for multiple traits - single SNP association
with Genome Wide Association Studies ('GWAS') summary statistics, Gene-based
Association Test that uses an extended Simes procedure ('GATES'), Hybrid
Set-based Test ('HYST') and extended version of GATES test for pathway-based
association testing ('GATES-Simes'). ).  The tests can be used with genetic and
other data sets with covariates.  The response variable is binary or
quantitative.  Summary; (1) Single trait-'SNP set association with
individual-level data ('aSPU', aSPUw', aSPUr'), (2) Single trait-'SNP set
association with summary statistics ('aSPUs'), (3) Single trait-pathway
association with individual-level data ('aSPUpath'), (4) Single trait-pathway
association with summary statistics ('aSPUsPath'), (5) Multiple traits-single
SNP association with individual-level data ('GEEaSPU'), (6) Multiple traits-
single SNP association with summary statistics ('MTaSPUs'), (7) Multiple
traits-'SNP set association with summary statistics('MTaSPUsSet'), (8) Multiple
traits-pathway association with summary statistics('MTaSPUsSetPath').")
    (license license:gpl3)))

(define-public r-aspline
  (package
    (name "r-aspline")
    (version "0.2.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "aspline" version))
              (sha256
               (base32
                "1a68x6jvsaxviy2w361f19iqzsdsaf9kcqw5cknf4yz9fvkqhjny"))))
    (properties `((upstream-name . "aspline")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-splines2
                             r-rlang
                             r-rcpp
                             r-mgcv
                             r-magrittr
                             r-ggplot2
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/goepp/aspline")
    (synopsis "Spline Regression with Adaptive Knot Selection")
    (description
     "Perform one-dimensional spline regression with automatic knot selection.  This
package uses a penalized approach to select the most relevant knots.  B-splines
of any degree can be fitted.  More details in Goepp et al. (2018)', \"Spline
Regression with Automatic Knot Selection\", <arXiv:1808.01770>.")
    (license license:gpl3)))

(define-public r-aspect
  (package
    (name "r-aspect")
    (version "1.0-6")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "aspect" version))
              (sha256
               (base32
                "13pb1pslyka706v13b7hdrzzn5bxmj2l5irpd9f1pm1n8a1ivrrl"))))
    (properties `((upstream-name . "aspect")))
    (build-system r-build-system)
    (home-page "https://r-forge.r-project.org/projects/psychor/")
    (synopsis
     "General Framework for Multivariate Analysis with Optimal Scaling")
    (description
     "This package contains various functions for optimal scaling.  One function
performs optimal scaling by maximizing an aspect (i.e.  a target function such
as the sum of eigenvalues, sum of squared correlations, squared multiple
correlations, etc.) of the corresponding correlation matrix.  Another function
performs implements the LINEALS approach for optimal scaling by minimization of
an aspect based on pairwise correlations and correlation ratios.  The resulting
correlation matrix and category scores can be used for further multivariate
methods such as structural equation models.")
    (license license:gpl2)))

(define-public r-aspc
  (package
    (name "r-aspc")
    (version "0.1.2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "aSPC" version))
              (sha256
               (base32
                "1q301rw7dax5v58srg4jlcam1qq2igkaj7kg8wlnlml0hsck4c4a"))))
    (properties `((upstream-name . "aSPC")))
    (build-system r-build-system)
    (propagated-inputs (list r-mvtnorm r-energy))
    (home-page "https://cran.r-project.org/package=aSPC")
    (synopsis
     "An Adaptive Sum of Powered Correlation Test (aSPC) for Global Association Between Two Random Vectors")
    (description
     "The aSPC test is designed to test global association between two groups of
variables potentially with moderate to high dimension (e.g. in hundreds).  The
aSPC is particularly useful when the association signals between two groups of
variables are sparse.")
    (license license:gpl3)))

(define-public r-asnipe
  (package
    (name "r-asnipe")
    (version "1.1.16")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "asnipe" version))
              (sha256
               (base32
                "0ky4v85gry8r265z8p7mi9kzq6j3s032jg4wddkzjjqgxzyzjl5y"))))
    (properties `((upstream-name . "asnipe")))
    (build-system r-build-system)
    (propagated-inputs (list r-matrix r-mass))
    (home-page "https://cran.r-project.org/package=asnipe")
    (synopsis
     "Animal Social Network Inference and Permutations for Ecologists")
    (description
     "This package implements several tools that are used in animal social network
analysis, as described in Whitehead (2007) Analyzing Animal Societies
<University of Chicago Press> and Farine & Whitehead (2015) <doi:
10.1111/1365-2656.12418>.  In particular, this package provides the tools to
infer groups and generate networks from observation data, perform permutation
tests on the data, calculate lagged association rates, and performed multiple
regression analysis on social network data.")
    (license license:gpl2)))

(define-public r-asmap
  (package
    (name "r-asmap")
    (version "1.0-4")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ASMap" version))
              (sha256
               (base32
                "0xnrl8jhbvbc789w5gc9dz7j7gzc7wsc94a3d2wdplrmxn186nrb"))))
    (properties `((upstream-name . "ASMap")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcolorbrewer r-qtl r-lattice r-gtools r-fields))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=ASMap")
    (synopsis "Linkage Map Construction using the MSTmap Algorithm")
    (description
     "This package provides functions for Accurate and Speedy linkage map
construction, manipulation and diagnosis of Doubled Haploid, Backcross and
Recombinant Inbred R/qtl objects.  This includes extremely fast linkage map
clustering and optimal marker ordering using MSTmap (see Wu et al.,2008).")
    (license license:gpl2+)))

(define-public r-aslib
  (package
    (name "r-aslib")
    (version "0.1.2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "aslib" version))
              (sha256
               (base32
                "1hy0ncanc3mb20yrby8s9hd8v2fg3x41vkj0jwl2b8znzl5n5b2n"))))
    (properties `((upstream-name . "aslib")))
    (build-system r-build-system)
    (propagated-inputs (list r-yaml
                             r-stringr
                             r-rweka
                             r-reshape2
                             r-plyr
                             r-paramhelpers
                             r-parallelmap
                             r-mlr
                             r-llama
                             r-ggplot2
                             r-data-table
                             r-corrplot
                             r-checkmate
                             r-bbmisc
                             r-batchtools))
    (home-page "https://github.com/coseal/aslib-r/")
    (synopsis "Interface to the Algorithm Selection Benchmark Library")
    (description
     "This package provides an interface to the algorithm selection benchmark library
at <http://www.aslib.net> and the LLAMA package
(<https://cran.r-project.org/package=llama>) for building algorithm selection
models; see Bischl et al. (2016) <doi:10.1016/j.artint.2016.04.003>.")
    (license license:gpl3)))

(define-public r-asip
  (package
    (name "r-asip")
    (version "0.4.9")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ASIP" version))
              (sha256
               (base32
                "06f1nvy920vyx3bmdi77mwvfsn32xsfxaslhagnf1zh652vfkbwi"))))
    (properties `((upstream-name . "ASIP")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr r-rgdal r-raster))
    (home-page "https://cran.r-project.org/package=ASIP")
    (synopsis "Automated Satellite Image Processing")
    (description
     "Efficiently perform complex satellite image processes automatically with minimum
inputs.  Functions are providing more control on the user to specify how the
function needs to be executed by offering more customization options and
facilitate more functionalities.  The functions are designed to identify the
type of input satellite images and perform accordingly.  Also, some functions
are giving options to perform multiple satellite data (even from different
types) in single run.  Package currently supports satellite images from most
widely used Landsat 4,5,7 and 8 and Sentinel-2 MSI data.  The primary
applications of this package are given below.  1.  Conversion of optical bands
to top of atmosphere reflectance.  2.  Conversion of thermal bands to
corresponding temperature images.  3.  Derive application oriented products
directly from source satellite image bands.  4.  Compute user defined equation
and produce corresponding image product.  5.  Other basic tools for satellite
image processing.  REFERENCES. i.  Chander and Markham (2003)
<doi:10.1109/TGRS.2003.818464>.  ii.  Roy et.al, (2014)
<doi:10.1016/j.rse.2014.02.001>.  iii.  Abrams (2000)
<doi:10.1080/014311600210326>.")
    (license license:gpl3)))

(define-public r-asioheaders
  (package
    (name "r-asioheaders")
    (version "1.22.1-1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AsioHeaders" version))
              (sha256
               (base32
                "15cd85zkjzpz321pnnjwn0g2v4rza6cdqanx89p5j3nrfihjrh32"))))
    (properties `((upstream-name . "AsioHeaders")))
    (build-system r-build-system)
    (home-page "https://github.com/eddelbuettel/asioheaders")
    (synopsis "'Asio' C++ Header Files")
    (description
     "Asio is a cross-platform C++ library for network and low-level I/O programming
that provides developers with a consistent asynchronous model using a modern C++
approach.  It is also included in Boost but requires linking when used with
Boost.  Standalone it can be used header-only (provided a recent compiler).
Asio is written and maintained by Christopher M. Kohlhoff, and released under
the Boost Software License', Version 1.0.")
    (license (license:fsdg-compatible "BSL-1.0"))))

(define-public r-asht
  (package
    (name "r-asht")
    (version "0.9.8")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "asht" version))
              (sha256
               (base32
                "0l0nmjz4vgqv3n36868k3zc47a504953dqma20fb20w482vns4zj"))))
    (properties `((upstream-name . "asht")))
    (build-system r-build-system)
    (propagated-inputs (list r-ssanv
                             r-perm
                             r-exactci
                             r-exact2x2
                             r-coin
                             r-bpcp))
    (home-page "https://cran.r-project.org/package=asht")
    (synopsis "Applied Statistical Hypothesis Tests")
    (description
     "Gives some hypothesis test functions (sign test, median and other quantile
tests, Wilcoxon signed rank test, coefficient of variation test, test of normal
variance, test on weighted sums of Poisson [see Fay and Kim
<doi:10.1002/bimj.201600111>], sample size for t-tests with different variances
and non-equal n per arm, Behrens-Fisher test, nonparametric ABC intervals,
Wilcoxon-Mann-Whitney test [with effect estimates and confidence intervals, see
Fay and Malinovsky <doi:10.1002/sim.7890>], two-sample melding tests [see Fay,
Proschan, and Brittain <doi:10.1111/biom.12231>], one-way ANOVA allowing
var.equal=FALSE [see Brown and Forsythe, 1974, Biometrics]), prevalence
confidence intervals that adjust for sensitivity and specificity [see Lang and
Reiczigel, 2014 <doi:10.1016/j.prevetmed.2013.09.015>]).  The focus is on
hypothesis tests that have compatible confidence intervals, but some functions
only have confidence intervals (e.g., prevSeSp).")
    (license license:gpl3)))

(define-public r-asgs-foyer
  (package
    (name "r-asgs-foyer")
    (version "0.3.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ASGS.foyer" version))
              (sha256
               (base32
                "089c4vm629rni0dfgg3r2a9s9yisdx1qs2dwssg44qw1w4hf1f50"))))
    (properties `((upstream-name . "ASGS.foyer")))
    (build-system r-build-system)
    (propagated-inputs (list r-sp))
    (home-page "https://cran.r-project.org/package=ASGS.foyer")
    (synopsis "Interface to the Australian Statistical Geography Standard")
    (description
     "The Australian Statistical Geography Standard ('ASGS') is a set of shapefiles by
the Australian Bureau of Statistics.  This package provides an interface to
those shapefiles, as well as methods for converting coordinates to shapefiles.")
    (license (license:fsdg-compatible "MPL"))))

(define-public r-asdreader
  (package
    (name "r-asdreader")
    (version "0.1-3")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "asdreader" version))
              (sha256
               (base32
                "15a922aw0v5w4hrha03xifx8cpifcc773gambgwqq6i5nz08ya26"))))
    (properties `((upstream-name . "asdreader")))
    (build-system r-build-system)
    (home-page "http://github.com/pierreroudier/asdreader")
    (synopsis "Reading ASD Binary Files in R")
    (description
     "This package provides a simple driver that reads binary data created by the ASD
Inc.  portable spectrometer instruments, such as the FieldSpec (for more
information, see <http://www.asdi.com/products/fieldspec-spectroradiometers>).
Spectral data can be extracted from the ASD files as raw (DN), white reference,
radiance, or reflectance.  Additionally, the metadata information contained in
the ASD file header can also be accessed.")
    (license license:gpl3)))

(define-public r-ascotracer
  (package
    (name "r-ascotracer")
    (version "0.0.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ascotraceR" version))
              (sha256
               (base32
                "0h7q49pdchw0apyrm813qrl4sp6hym31awh1bjlk06fd76ynj72y"))))
    (properties `((upstream-name . "ascotraceR")))
    (build-system r-build-system)
    (propagated-inputs (list r-terra
                             r-sf
                             r-purrr
                             r-lutz
                             r-lubridate
                             r-data-table
                             r-circular))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/IhsanKhaliq/ascotraceR")
    (synopsis "Simulate the Spread of Ascochyta Blight in Chickpea")
    (description
     "This package provides a spatiotemporal model that simulates the spread of
Ascochyta blight in chickpea fields based on location-specific weather
conditions.  This model is adapted from a model developed by Diggle et al.
(2002) <doi:10.1094/PHYTO.2002.92.10.1110> for simulating the spread of
anthracnose in a lupin field.")
    (license license:expat)))

(define-public r-asciisetupreader
  (package
    (name "r-asciisetupreader")
    (version "2.4.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "asciiSetupReader" version))
              (sha256
               (base32
                "02s3p0qqa9h1kyx96c29blwgfkdm50p10kr14wklh19gibiznyfj"))))
    (properties `((upstream-name . "asciiSetupReader")))
    (build-system r-build-system)
    (propagated-inputs (list r-zoo
                             r-vroom
                             r-stringr
                             r-shiny
                             r-rstudioapi
                             r-readr
                             r-miniui
                             r-haven
                             r-data-table))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/jacobkap/asciiSetupReader")
    (synopsis
     "Reads Fixed-Width ASCII Data Files (.txt or .dat) that Have Accompanying Setup Files (.sps or .sas)")
    (description
     "Lets you open a fixed-width ASCII file (.txt or .dat) that has an accompanying
setup file (.sps or .sas).  These file combinations are sometimes referred to as
.txt+.sps, .txt+.sas, .dat+.sps, or .dat+.sas.  This will only run in a txt-sps
or txt-sas pair in which the setup file contains instructions to open that text
file.  It will NOT open other text files, .sav, .sas, or .por data files.
Fixed-width ASCII files with setup files are common in older (pre-2000)
government data.")
    (license license:expat)))

(define-public r-asciiruler
  (package
    (name "r-asciiruler")
    (version "0.2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "asciiruler" version))
              (sha256
               (base32
                "0xhkbsy9dypk09avazgxczyfkh3rhdxhwci688dw1lxnhxv1hj24"))))
    (properties `((upstream-name . "asciiruler")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr))
    (home-page "https://cran.r-project.org/package=asciiruler")
    (synopsis "Render an ASCII Ruler")
    (description
     "An ASCII ruler is for measuring text and is especially useful for sequence
analysis.  Included in this package are methods to create ASCII rulers and
associated GenBank sequence blocks, multi-column text displays that make it easy
for viewers to locate nucleotides by position.")
    (license (list license:gpl3
                   (license:fsdg-compatible "file://LICENSE")))))

(define-public r-asciichartr
  (package
    (name "r-asciichartr")
    (version "0.1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "asciichartr" version))
              (sha256
               (base32
                "1b73bbysnxy3x3gwhm80xry45m18yh716wrc93v1awk3c1p2cv3m"))))
    (properties `((upstream-name . "asciichartr")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=asciichartr")
    (synopsis "Lightweight ASCII Line Graphs")
    (description
     "Create ASCII line graphs of a time series directly on your terminal in an easy
way.  There are some configurations you can add to make the plot the way you
like.  This project was inspired by the original asciichart package by Igor
Kroitor.")
    (license license:expat)))

(define-public r-asciicast
  (package
    (name "r-asciicast")
    (version "2.2.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "asciicast" version))
              (sha256
               (base32
                "1x3dr3lr5hz53xl0z4y4i10qfmp8jakvr0r0jglcz3r66ajcghhk"))))
    (properties `((upstream-name . "asciicast")))
    (build-system r-build-system)
    (propagated-inputs (list r-withr
                             r-v8
                             r-tibble
                             r-processx
                             r-magick
                             r-jsonlite
                             r-curl
                             r-cli))
    (home-page "https://github.com/r-lib/asciicast")
    (synopsis "Create 'Ascii' Screen Casts from R Scripts")
    (description
     "Record asciicast screen casts from R scripts.  Convert them to animated SVG
images, to be used in README files, or blog posts.  Includes asciinema-player as
an HTML widget, and an asciicast knitr engine, to embed ascii screen casts in
Rmarkdown documents.")
    (license license:expat)))

(define-public r-ascii
  (package
    (name "r-ascii")
    (version "2.4")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ascii" version))
              (sha256
               (base32
                "0k675an7sl00bslx4yb6vvvgnp1kl244cfjljv632asqdm3rkmrv"))))
    (properties `((upstream-name . "ascii")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival r-digest r-codetools))
    (home-page "https://github.com/mclements/ascii")
    (synopsis "Export R Objects to Several Markup Languages")
    (description
     "Coerce R object to asciidoc', txt2tags', restructuredText', org', textile or
pandoc syntax.  Package comes with a set of drivers for Sweave'.")
    (license license:gpl2+)))

(define-public r-ascenttraining
  (package
    (name "r-ascenttraining")
    (version "1.0.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ascentTraining" version))
              (sha256
               (base32
                "1dwmr33jc2fp9x51kzlqa4vib7xmzvz9a7qlfgvhxhld2bxlrrgi"))))
    (properties `((upstream-name . "ascentTraining")))
    (build-system r-build-system)
    (home-page "https://www.ascent.io/")
    (synopsis "Ascent Training Datasets")
    (description
     "Datasets to be used primarily in conjunction with Ascent training materials but
also for the book SAMS Teach Yourself R in 24 Hours (ISBN: 978-0-672-33848-9).
Version 1.0-7 is largely for use with the book; however, version 1.1 has a much
greater focus on use with training materials, whilst retaining compatibility
with the book.")
    (license license:gpl2)))

(define-public r-asbio
  (package
    (name "r-asbio")
    (version "1.8-3")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "asbio" version))
              (sha256
               (base32
                "1p0hfgkfcnxdf2jivn1mm3rjdqs4arik6ajc1gc1mmdwfwh82s5x"))))
    (properties `((upstream-name . "asbio")))
    (build-system r-build-system)
    (inputs (list))
    (propagated-inputs (list r-scatterplot3d
                             r-plotrix
                             r-pixmap
                             r-mvtnorm
                             r-multcompview
                             r-lattice
                             r-gwidgets2tcltk
                             r-gwidgets2
                             r-desolve))
    (home-page "https://cran.r-project.org/package=asbio")
    (synopsis "Collection of Statistical Tools for Biologists")
    (description
     "This package contains functions from: Aho, K. (2014) Foundational and Applied
Statistics for Biologists using R. CRC/Taylor and Francis, Boca Raton, FL, ISBN:
978-1-4398-7338-0.")
    (license license:gpl2+)))

(define-public r-asaur
  (package
    (name "r-asaur")
    (version "0.50")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "asaur" version))
              (sha256
               (base32
                "0c1rgic76w3i2xhna7i52lyc0p01s5b1mxyn55gqw6i19v9mq0b3"))))
    (properties `((upstream-name . "asaur")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=asaur")
    (synopsis "Data Sets for \"Applied Survival Analysis Using R\"\"")
    (description
     "Data sets are referred to in the text \"Applied Survival Analysis Using R\" by
Dirk F. Moore, Springer, 2016, ISBN: 978-3-319-31243-9,
<DOI:10.1007/978-3-319-31245-3>.")
    (license license:cc0)))

(define-public r-arxiv
  (package
    (name "r-arxiv")
    (version "0.6")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "aRxiv" version))
              (sha256
               (base32
                "1smv7aiqdk60aq9lna33a7hdykjdgfakaycpqkjj711b3pixcd34"))))
    (properties `((upstream-name . "aRxiv")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml r-httr))
    (native-inputs (list r-knitr))
    (home-page "https://docs.ropensci.org/aRxiv/")
    (synopsis "Interface to the arXiv API")
    (description
     "An interface to the API for arXiv', a repository of electronic preprints for
computer science, mathematics, physics, quantitative biology, quantitative
finance, and statistics.")
    (license license:expat)))

(define-public r-arulesviz
  (package
    (name "r-arulesviz")
    (version "1.5-1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "arulesViz" version))
              (sha256
               (base32
                "06mqdqg5amcrb75lf77wilb9v8c7f50b54p0pk76q0jvirycqrzc"))))
    (properties `((upstream-name . "arulesViz")))
    (build-system r-build-system)
    (propagated-inputs (list r-visnetwork
                             r-vcd
                             r-tidyr
                             r-tibble
                             r-seriation
                             r-scatterplot3d
                             r-plotly
                             r-igraph
                             r-ggraph
                             r-ggplot2
                             r-dt
                             r-dplyr
                             r-arules))
    (home-page "https://github.com/mhahsler/arulesViz")
    (synopsis "Visualizing Association Rules and Frequent Itemsets")
    (description
     "Extends package arules with various visualization techniques for association
rules and itemsets.  The package also includes several interactive
visualizations for rule exploration.  Michael Hahsler (2017)
<doi:10.32614/RJ-2017-047>.")
    (license license:gpl3)))

(define-public r-arulessequences
  (package
    (name "r-arulessequences")
    (version "0.2-26")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "arulesSequences" version))
              (sha256
               (base32
                "09571bqqbf19w80nbs34k1zq54c6yyfcqm2a2jpkd41jmij6pvj5"))))
    (properties `((upstream-name . "arulesSequences")))
    (build-system r-build-system)
    (propagated-inputs (list r-arules))
    (home-page "https://cran.r-project.org/package=arulesSequences")
    (synopsis "Mining Frequent Sequences")
    (description
     "Add-on for arules to handle and mine frequent sequences.  Provides interfaces to
the C++ implementation of cSPADE by Mohammed J. Zaki.")
    (license license:gpl2)))

(define-public r-arulesnbminer
  (package
    (name "r-arulesnbminer")
    (version "0.1-8")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "arulesNBMiner" version))
              (sha256
               (base32
                "0kqvi7dzq3mrn6cq22gwxh4p54mgfn9s1sd2cfnbw1f9zp078lsn"))))
    (properties `((upstream-name . "arulesNBMiner")))
    (build-system r-build-system)
    (inputs (list openjdk))
    (propagated-inputs (list r-rjava r-arules))
    (home-page "https://github.com/mhahsler/arulesNBMiner")
    (synopsis "Mining NB-Frequent Itemsets and NB-Precise Rules")
    (description
     "NBMiner is an implementation of the model-based mining algorithm for mining
NB-frequent itemsets and NB-precise rules.  Michael Hahsler (2006)
<doi:10.1007/s10618-005-0026-2>.")
    (license license:gpl2)))

(define-public r-arulescba
  (package
    (name "r-arulescba")
    (version "1.2.5")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "arulesCBA" version))
              (sha256
               (base32
                "13p876k3wg84khvzf6kkjpna0l9yjxyq43nh9dnpma7sidq5ldi0"))))
    (properties `((upstream-name . "arulesCBA")))
    (build-system r-build-system)
    (inputs (list openjdk))
    (propagated-inputs (list r-matrix r-glmnet r-discretization r-arules))
    (home-page "https://github.com/mhahsler/arulesCBA")
    (synopsis "Classification Based on Association Rules")
    (description
     "This package provides the infrastructure for association rule-based
classification including the algorithms CBA, CMAR, CPAR, C4.5, FOIL, PART, PRM,
RCAR, and RIPPER to build associative classifiers.  Hahsler et al (2019)
<doi:10.32614/RJ-2019-048>.")
    (license license:gpl3)))

(define-public r-artsy
  (package
    (name "r-artsy")
    (version "0.2.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "aRtsy" version))
              (sha256
               (base32
                "195022z55733vi52kz739fwk49zvsifnma0z98zcgzymynyqq0ki"))))
    (properties `((upstream-name . "aRtsy")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpparmadillo
                             r-rcpp
                             r-randomforest
                             r-kknn
                             r-ggplot2
                             r-e1071
                             r-ambient))
    (home-page "https://koenderks.github.io/aRtsy/")
    (synopsis "Generative Art with 'ggplot2'")
    (description
     "This package provides algorithms for creating artworks in the ggplot2 language
that incorporate some form of randomness.")
    (license license:gpl3+)))

(define-public r-artp2
  (package
    (name "r-artp2")
    (version "0.9.45")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ARTP2" version))
              (sha256
               (base32
                "12nqxry2jkl1n07rbms38mrnp39cn00d0h272d9f1z5x883flv62"))))
    (properties `((upstream-name . "ARTP2")))
    (build-system r-build-system)
    (propagated-inputs (list r-formula r-data-table))
    (home-page "https://github.com/zhangh12/ARTP2")
    (synopsis "Pathway and Gene-Level Association Test")
    (description
     "Pathway and gene level association test using raw data or summary statistics.")
    (license (list license:gpl2 license:gpl3))))

(define-public r-artool
  (package
    (name "r-artool")
    (version "0.11.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ARTool" version))
              (sha256
               (base32
                "16awxcncyhry0ygk8gdvlff787837rr8qsyg1pxd11w4v1llrqrf"))))
    (properties `((upstream-name . "ARTool")))
    (build-system r-build-system)
    (propagated-inputs (list r-plyr
                             r-magrittr
                             r-lme4
                             r-emmeans
                             r-dplyr
                             r-car))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/mjskay/ARTool/")
    (synopsis "Aligned Rank Transform")
    (description
     "The aligned rank transform for nonparametric factorial ANOVAs as described by
Wobbrock, Findlater, Gergle, and Higgins (2011) <doi:10.1145/1978942.1978963>.
Also supports aligned rank transform contrasts as described by Elkin, Kay,
Higgins, and Wobbrock (2021) <doi:10.1145/3472749.3474784>.")
    (license license:gpl2+)))

(define-public r-artofr
  (package
    (name "r-artofr")
    (version "0.4.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ARTofR" version))
              (sha256
               (base32
                "1dw9aascnqr5cbk8a862rlma94b39ndgkrhf826qf4k58y92nf5q"))))
    (properties `((upstream-name . "ARTofR")))
    (build-system r-build-system)
    (propagated-inputs (list r-shiny r-rstudioapi r-clipr r-bannercommenter))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=ARTofR")
    (synopsis "To Insert Title, Divider, and Block of Comments")
    (description
     "For instructions, check <https://github.com/Hzhang-ouce/ARTofR>.  This is a
wrapper of bannerCommenter', for inserting neat comments, headers and dividers.")
    (license license:expat)))

(define-public r-arthistory
  (package
    (name "r-arthistory")
    (version "0.1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "arthistory" version))
              (sha256
               (base32
                "01jw0r3pmwwrs5cb31pjyf5cygnfqzyim2dw45lqd0yywkmc5y3h"))))
    (properties `((upstream-name . "arthistory")))
    (build-system r-build-system)
    (home-page "https://github.com/saralemus7/arthistory")
    (synopsis "Art History Textbook Data")
    (description
     "Data from Gardner and Janson art history textbooks about both the artists
featured in these books as well as their works.  See Helen Gardner (\"Art through
the ages; an introduction to its history and significance,\" 1926,
<https://find.library.duke.edu/catalog/DUKE000104481>.  Helen Gardner, revised
by Horst de la Croix and Richard G. Tansey (\"Gardner’s Art through the ages,\"
1980, ISBN: 0155037587).  Fred S. Kleiner (\"Gardner’s art through the ages: a
global history,\" 2020, ISBN: 9781337630702).  Horst de la Croix and Richard G.
Tansey (\"Gardner's art through the ages,\" 1986, ISBN: 0155037633).  Helen
Gardner (\"Art through the ages; an introduction to its history and
significance,\" 1936, <https://find.library.duke.edu/catalog/DUKE001199463>).
Helen Gardner (\"Art through the ages,\" 1948,
<https://find.library.duke.edu/catalog/DUKE001199466>).  Helen Gardner, revised
under the editorship of Sumner M. Crosby (\"Art through the ages,\" 1959,
<https://find.library.duke.edu/catalog/DUKE001199469>).  Helen Gardner, revised
by Horst de la Croix and Richard G. Tansey (\"Gardner’s Art through the ages,\"
1975, ISBN: 0155037560).  Fred S. Kleiner (\"Gardner’s Art through the ages: a
global history,\" 2013, ISBN: 9780495915423.  Fred S. Kleiner, Christin J.
Mamiya, Richard G. Tansey (\"Gardner’s art through the ages,\" 2001, ISBN:
0155083155).  Fred S. Kleiner (\"Gardner’s Art through the ages: a global
history,\" 2016, ISBN: 9781285837840).  Fred S. Kleiner, Christin J. Mamiya
(\"Gardner’s art through the ages,\" 2005, ISBN: 0534640958).  Helen Gardner,
revised by Horst de la Croix and Richard G. Tansey (\"Gardner’s Art through the
ages,\" 1970, ISBN: 0155037528).  Helen Gardner, Richard G. Tansey, Fred S.
Kleiner (\"Gardner’s Art through the ages,\" 1996, ISBN: 0155011413).  Helen
Gardner, Horst de la Croix, Richard G. Tansey, Diane Kirkpatrick (\"Gardner’s
Art through the ages,\" 1991, ISBN: 0155037692).  Helen Gardner, Fred S. Kleiner
(\"Gardner’s Art through the ages: a global history,\" 2009, ISBN:
9780495093077).  Davies, Penelope J.E., Walter B. Denny, Frima Fox Hofrichter,
Joseph F. Jacobs, Ann S. Roberts, David L. Simon (\"Janson’s history of art:
the western tradition,\" 2007, ISBN: 0131934554).  Davies, Penelope J.E., Walter
B. Denny, Frima Fox Hofrichter, Joseph F. Jacobs, Ann S. Roberts, David L. Simon
(\"Janson’s history of art: the western tradition,\" 2011, ISBN: 9780205685172).
 H. W. Janson, Anthony F. Janson (\"History of Art,\" 2001, ISBN: 0810934469).  H.
W. Janson, revised and expanded by Anthony F. Janson (\"History of art,\" 1986,
ISBN: 013389388).  H. W. Janson, Dora Jane Janson (\"History of art: a survey of
the major visual arts from the dawn of history to present day,\" 1977, ISBN:
0810910527).  H. W. Janson, Dora Jane Janson (\"History of art: a survey of the
major visual arts from the dawn of history to present day,\" 1969,
<https://find.library.duke.edu/catalog/DUKE000005734>).  H. W. Janson, Dora Jane
Janson (\"History of art: a survey of the major visual arts from the dawn of
history to present day,\" 1963,
<https://find.library.duke.edu/catalog/DUKE001521852>).  H. W. Janson, revised
and expanded by Anthony F. Janson (\"History of art,\" 1991, ISBN: 0810934019).
H. W. Janson, revised and expanded by Anthony F. Janson (\"History of art,\" 1995,
ISBN: 0810934213).")
    (license license:expat)))

(define-public r-artfima
  (package
    (name "r-artfima")
    (version "1.5")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "artfima" version))
              (sha256
               (base32
                "1nqsq9fsqk9kag9n7i2r9yvf578nkdfrkkv7qy8650prka0jca2p"))))
    (properties `((upstream-name . "artfima")))
    (build-system r-build-system)
    (propagated-inputs (list r-ltsa r-gsl))
    (home-page "http://www.stats.uwo.ca/faculty/aim")
    (synopsis "ARTFIMA Model Estimation")
    (description
     "Fit and simulate ARTFIMA. Theoretical autocovariance function and spectral
density function for stationary ARTFIMA.")
    (license license:gpl2+)))

(define-public r-art
  (package
    (name "r-art")
    (version "1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ART" version))
              (sha256
               (base32
                "186w1ivj5v3h906crl953qxgai5wiznaih83dgvwgnmabs9p1wvk"))))
    (properties `((upstream-name . "ART")))
    (build-system r-build-system)
    (propagated-inputs (list r-car))
    (home-page "http://decsai.ugr.es/~pjvi/r-packages.html")
    (synopsis "Aligned Rank Transform for Nonparametric Factorial Analysis")
    (description
     "An implementation of the Aligned Rank Transform technique for factorial analysis
(see references below for details) including models with missing terms
(unsaturated factorial models).  The function first computes a separate aligned
ranked response variable for each effect of the user-specified model, and then
runs a classic ANOVA on each of the aligned ranked responses.  For further
details, see Higgins, J. J. and Tashtoush, S. (1994).  An aligned rank transform
test for interaction.  Nonlinear World 1 (2), pp.  201-211.  Wobbrock, J.O.,
Findlater, L., Gergle, D. and Higgins,J.J. (2011).  The Aligned Rank Transform
for nonparametric factorial analyses using only ANOVA procedures.  Proceedings
of the ACM Conference on Human Factors in Computing Systems (CHI 11).  New York:
ACM Press, pp.  143-146. <doi:10.1145/1978942.1978963>.")
    (license license:lgpl3+)))

(define-public r-arse
  (package
    (name "r-arse")
    (version "1.0.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "arse" version))
              (sha256
               (base32
                "0ssaalc058m09gfcr1n0s729rx2plia3zkhlynj67drclyvhyb0i"))))
    (properties `((upstream-name . "arse")))
    (build-system r-build-system)
    (propagated-inputs (list r-pracma r-dplyr))
    (home-page "https://github.com/nr3xe/arse")
    (synopsis "Area of Resilience to Stress Event")
    (description
     "This package provides a method for quantifying resilience after a stress event.
A set of functions calculate the area of resilience that is created by the
departure of baseline y (i.e., robustness) and the time taken x to return to
baseline (i.e., rapidity) after a stress event using the Cartesian coordinates
of the data.  This package has the capability to calculate areas of resilience,
growth, and cases in which resilience is not achieved (e.g., diminished
performance without return to baseline).")
    (license license:expat)))

(define-public r-ars
  (package
    (name "r-ars")
    (version "0.6")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ars" version))
              (sha256
               (base32
                "0zs1rk3i7pc9wcvxrvjcls194mfbvmkz7cb6pwd1cm3fzjwsyxsp"))))
    (properties `((upstream-name . "ars")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=ars")
    (synopsis "Adaptive Rejection Sampling")
    (description "Adaptive Rejection Sampling, Original version.")
    (license license:gpl2+)))

(define-public r-arrayhelpers
  (package
    (name "r-arrayhelpers")
    (version "1.1-0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "arrayhelpers" version))
              (sha256
               (base32
                "02rl530qxi1idiqpmzg5wr9vl5c7phizhpj64k5pn8xq9zfxbpaz"))))
    (properties `((upstream-name . "arrayhelpers")))
    (build-system r-build-system)
    (propagated-inputs (list r-svunit))
    (home-page "http://arrayhelpers.r-forge.r-project.org/")
    (synopsis "Convenience Functions for Arrays")
    (description "Some convenient functions to work with arrays.")
    (license (list license:gpl2+ license:gpl3+))))

(define-public r-arrapply
  (package
    (name "r-arrapply")
    (version "2.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "arrApply" version))
              (sha256
               (base32
                "0qy7iwi580rrf3sycsbv6qgxsqcdy9pdbnkdrx81j68qni9iw737"))))
    (properties `((upstream-name . "arrApply")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpparmadillo r-rcpp))
    (home-page "https://cran.r-project.org/package=arrApply")
    (synopsis "Apply a Function to a Margin of an Array")
    (description
     "High performance variant of apply() for a fixed set of functions.  Considerable
speedup is a trade-off for universality, user defined functions cannot be used
with this package.  However, 21 most currently employed functions are available
for usage.  They can be divided in three types: reducing functions (like mean(),
sum() etc., giving a scalar when applied to a vector), mapping function (like
normalise(), cumsum() etc., giving a vector of the same length as the input
vector) and finally, vector reducing function (like diff() which produces result
vector of a length different from the length of input vector).  Optional or
mandatory additional arguments required by some functions (e.g. norm type for
norm() or normalise() functions) can be passed as named arguments in ...'.")
    (license license:gpl2+)))

(define-public r-arrangements
  (package
    (name "r-arrangements")
    (version "1.1.9")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "arrangements" version))
              (sha256
               (base32
                "0nrlyxgn6667l2rb1q5rvps1anld9aq88qqr3ch2i6zchnqxrdg9"))))
    (properties `((upstream-name . "arrangements")))
    (build-system r-build-system)
    (inputs (list gmp))
    (propagated-inputs (list r-r6 r-gmp))
    (home-page "https://github.com/randy3k/arrangements")
    (synopsis
     "Fast Generators and Iterators for Permutations, Combinations, Integer Partitions and Compositions")
    (description
     "Fast generators and iterators for permutations, combinations, integer partitions
and compositions.  The arrangements are in lexicographical order and generated
iteratively in a memory efficient manner.  It has been demonstrated that
arrangements outperforms most existing packages of similar kind.  Benchmarks
could be found at
<https://randy3k.github.io/arrangements/articles/benchmark.html>.")
    (license license:expat)))

(define-public r-arpsdca
  (package
    (name "r-arpsdca")
    (version "1.1.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "aRpsDCA" version))
              (sha256
               (base32
                "0ghg43rd6bnv4jp8pkpd1ixp5l6kq5pr0mxq61q24s24g0m3s64p"))))
    (properties `((upstream-name . "aRpsDCA")))
    (build-system r-build-system)
    (home-page "https://github.com/derrickturk/aRpsDCA")
    (synopsis "Arps Decline Curve Analysis in R")
    (description
     "This package provides functions for Arps decline-curve analysis on oil and gas
data.  Includes exponential, hyperbolic, harmonic, and hyperbolic-to-exponential
models as well as the preceding with initial curtailment or a period of linear
rate buildup.  Functions included for computing rate, cumulative production,
instantaneous decline, EUR, time to economic limit, and performing least-squares
best fits.")
    (license license:lgpl2.1)))

(define-public r-arpr
  (package
    (name "r-arpr")
    (version "0.1.2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "arpr" version))
              (sha256
               (base32
                "02qsvmgnyr7aqgpij8m5yg9cww8wbrg6a33vxxvy3sl9v5f7vzh5"))))
    (properties `((upstream-name . "arpr")))
    (build-system r-build-system)
    (propagated-inputs (list r-rlang r-magrittr))
    (home-page "https://github.com/statnmap/arpr")
    (synopsis "Advanced R Pipes")
    (description
     "This package provides convenience functions for programming with magrittr pipes.
 Conditional pipes, a string prefixer and a function to pipe the given object
into a specific argument given by character name are currently supported.  It is
named after the dadaist Hans Arp, a friend of Rene Magritte.")
    (license license:gpl3+)))

(define-public r-arpobservation
  (package
    (name "r-arpobservation")
    (version "1.2.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ARPobservation" version))
              (sha256
               (base32
                "1gpq5wl3mwp4hi49h1g6nnizzpnfc19pv8chdyhv8y5sraq1k2ag"))))
    (properties `((upstream-name . "ARPobservation")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=ARPobservation")
    (synopsis
     "Tools for Simulating Direct Behavioral Observation Recording Procedures Based on Alternating Renewal Processes")
    (description
     "Tools for simulating data generated by direct observation recording.  Behavior
streams are simulated based on an alternating renewal process, given specified
distributions of event durations and interim times.  Different procedures for
recording data can then be applied to the simulated behavior streams.  Functions
are provided for the following recording methods: continuous duration recording,
event counting, momentary time sampling, partial interval recording, whole
interval recording, and augmented interval recording.")
    (license license:gpl3)))

(define-public r-arplmec
  (package
    (name "r-arplmec")
    (version "2.4.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ARpLMEC" version))
              (sha256
               (base32
                "1d6gvgbnj19dislzjlxn7i0iq7h56zz7hm9x5l865ji790b9smqw"))))
    (properties `((upstream-name . "ARpLMEC")))
    (build-system r-build-system)
    (propagated-inputs (list r-truncatednormal
                             r-relliptical
                             r-numderiv
                             r-mnormt
                             r-mass
                             r-laplacesdemon
                             r-expm))
    (home-page "https://cran.r-project.org/package=ARpLMEC")
    (synopsis
     "Censored Mixed-Effects Models with Different Correlation Structures")
    (description
     "Left, right or interval censored mixed-effects linear model with autoregressive
errors of order p or DEC correlation structure using the type-EM algorithm.  The
error distribution can be Normal or t-Student.  It provides the parameter
estimates, the standard errors and prediction of future observations (available
only for the normal case).  Olivari et all (2021)
<doi:10.1080/10543406.2020.1852246>.")
    (license license:gpl2+)))

(define-public r-arpaldata
  (package
    (name "r-arpaldata")
    (version "1.2.3")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ARPALData" version))
              (sha256
               (base32
                "1zpl3dpqkf9m9d4hqqmcbqb3dz8gcqyp0rhs8gvs5vgidsy5sjv8"))))
    (properties `((upstream-name . "ARPALData")))
    (build-system r-build-system)
    (propagated-inputs (list r-tm
                             r-tidyverse
                             r-tidyselect
                             r-tidyr
                             r-tibble
                             r-stringr
                             r-stringi
                             r-sf
                             r-rsocrata
                             r-rlang
                             r-readr
                             r-purrr
                             r-mondate
                             r-moments
                             r-magrittr
                             r-lubridate
                             r-ggplot2
                             r-eurostat
                             r-dplyr
                             r-doparallel
                             r-data-table
                             r-aweek))
    (home-page "https://cran.r-project.org/package=ARPALData")
    (synopsis
     "Retrieving, Managing and Analysing Air Quality and Weather Data for Lombardy (Italy) using ARPA Lombardia Open Database")
    (description
     "This package contains functions for retrieving, managing and analysing air
quality and weather data from Regione Lombardia open database
(<https://www.dati.lombardia.it/>).  Data are collected by ARPA Lombardia
(Lombardia Environmental Protection Agency), Italy, through its ground
monitoring network.  See the webpage
<https://www.arpalombardia.it/Pages/ARPA_Home_Page.aspx> for further information
on ARPA Lombardia's activities and history.  Data quality (e.g. missing values,
exported values, graphical mapping) has been checked involving members of the
ARPA Lombardia's office for air quality control.  The package makes available
observations since 1989 (for weather) and 1996 (for air quality) and are updated
with daily frequency by the regional agency.")
    (license license:gpl2+)))

(define-public r-arothron
  (package
    (name "r-arothron")
    (version "2.0.3")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "Arothron" version))
              (sha256
               (base32
                "0rb1n9pmp7q2wdihn26kbpyvyznlk8mrs8c26l1ar4q29jw44rw4"))))
    (properties `((upstream-name . "Arothron")))
    (build-system r-build-system)
    (propagated-inputs (list r-vegan
                             r-stringr
                             r-rvcg
                             r-rgl
                             r-morpho
                             r-geometry
                             r-foreach
                             r-doparallel
                             r-compositions
                             r-alphashape3d
                             r-abind))
    (home-page "https://cran.r-project.org/package=Arothron")
    (synopsis "Geometric Morphometric Methods and Virtual Anthropology Tools")
    (description
     "Tools for geometric morphometric analysis.  The package includes tools of
virtual anthropology to align two not articulated parts belonging to the same
specimen, to build virtual cavities as endocast (Profico et al, 2021
<doi:10.1002/ajpa.24340>).")
    (license license:gpl2)))

(define-public r-aroma-core
  (package
    (name "r-aroma-core")
    (version "3.3.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "aroma.core" version))
              (sha256
               (base32
                "12118xdb74c4b2ca5dq57zxkrrcjjji10b5a1qxpixkrc36bfskv"))))
    (properties `((upstream-name . "aroma.core")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcolorbrewer
                             r-r-utils
                             r-r-rsp
                             r-r-oo
                             r-r-methodss3
                             r-r-filesets
                             r-r-devices
                             r-r-cache
                             r-pscbs
                             r-matrixstats
                             r-listenv
                             r-future
                             r-biocmanager))
    (home-page "https://github.com/HenrikBengtsson/aroma.core")
    (synopsis
     "Core Methods and Classes Used by 'aroma.*' Packages Part of the Aroma Framework")
    (description
     "Core methods and classes used by higher-level aroma.* packages part of the Aroma
Project, e.g. aroma.affymetrix and aroma.cn'.")
    (license license:lgpl2.1+)))

(define-public r-aroma-cn
  (package
    (name "r-aroma-cn")
    (version "1.7.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "aroma.cn" version))
              (sha256
               (base32
                "0d4wgc9vyr89i1588zh61f5wjsizv9j5y0j8zhrw65r9y8ffwa0w"))))
    (properties `((upstream-name . "aroma.cn")))
    (build-system r-build-system)
    (propagated-inputs (list r-r-utils
                             r-r-oo
                             r-r-methodss3
                             r-r-filesets
                             r-r-cache
                             r-pscbs
                             r-matrixstats
                             r-future-apply
                             r-aroma-core))
    (home-page "https://www.aroma-project.org/")
    (synopsis "Copy-Number Analysis of Large Microarray Data Sets")
    (description
     "This package provides methods for analyzing DNA copy-number data.  Specifically,
this package implements the multi-source copy-number normalization (MSCN) method
for normalizing copy-number data obtained on various platforms and technologies.
 It also implements the TumorBoost method for normalizing paired tumor-normal
SNP data.")
    (license license:lgpl2.1+)))

(define-public r-aroma-apd
  (package
    (name "r-aroma-apd")
    (version "0.6.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "aroma.apd" version))
              (sha256
               (base32
                "0by8nss4m1hrd33bv9vdqgf67117a48y3wdkyc3q35anlz7kn3yk"))))
    (properties `((upstream-name . "aroma.apd")))
    (build-system r-build-system)
    (propagated-inputs (list r-r-utils r-r-oo r-r-methodss3 r-r-huge))
    (home-page "https://github.com/HenrikBengtsson/aroma.apd")
    (synopsis
     "Probe-Level Data File Format Used by 'aroma.affymetrix' [deprecated]")
    (description
     "DEPRECATED. Do not start building new projects based on this package. (The
(in-house) APD file format was initially developed to store Affymetrix
probe-level data, e.g. normalized CEL intensities.  Chip types can be added to
APD file and similar to methods in the affxparser package, this package provides
methods to read APDs organized by units (probesets).  In addition, the probe
elements can be arranged optimally such that the elements are guaranteed to be
read in order when, for instance, data is read unit by unit.  This speeds up the
read substantially.  This package is supporting the Aroma framework and should
not be used elsewhere.)")
    (license license:lgpl2.1+)))

(define-public r-aroma-affymetrix
  (package
    (name "r-aroma-affymetrix")
    (version "3.2.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "aroma.affymetrix" version))
              (sha256
               (base32
                "1yzmqh7f3x5mzws7azxa6rgqv8kcm861y9pc5ppc0vsgz7fvpvvs"))))
    (properties `((upstream-name . "aroma.affymetrix")))
    (build-system r-build-system)
    (propagated-inputs (list r-r-utils
                             r-r-oo
                             r-r-methodss3
                             r-r-filesets
                             r-r-devices
                             r-r-cache
                             r-matrixstats
                             r-mass
                             r-listenv
                             r-future
                             r-aroma-core
                             r-aroma-apd))
    (home-page "https://www.aroma-project.org/")
    (synopsis "Analysis of Large Affymetrix Microarray Data Sets")
    (description
     "This package provides a cross-platform R framework that facilitates processing
of any number of Affymetrix microarray samples regardless of computer system.
The only parameter that limits the number of chips that can be processed is the
amount of available disk space.  The Aroma Framework has successfully been used
in studies to process tens of thousands of arrays.  This package has actively
been used since 2006.")
    (license license:lgpl2.1+)))

(define-public r-aroc
  (package
    (name "r-aroc")
    (version "1.0-4")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AROC" version))
              (sha256
               (base32
                "0wwv63mlh8pl5pzaih57l2qy70fz2wpfyxns1lyp95sxhq7ddwza"))))
    (properties `((upstream-name . "AROC")))
    (build-system r-build-system)
    (propagated-inputs (list r-spatstat-geom
                             r-np
                             r-nor1mix
                             r-moments
                             r-matrix
                             r-mass
                             r-hmisc))
    (home-page "https://cran.r-project.org/package=AROC")
    (synopsis
     "Covariate-Adjusted Receiver Operating Characteristic Curve Inference")
    (description
     "Estimates the covariate-adjusted Receiver Operating Characteristic (AROC) curve
and pooled (unadjusted) ROC curve by different methods.  Inacio de Carvalho, V.,
and Rodriguez-Alvarez, M. X. (2018) <arXiv:1806.00473>.  NOTE: We have created a
new package, ROCnReg', with more functionalities.  It also implements all the
methods included in AROC'.  We, therefore, recommend using ROCnReg ('AROC will
no longer be maintained).")
    (license (list license:gpl2+ license:gpl3+))))

(define-public r-arnie
  (package
    (name "r-arnie")
    (version "0.1.2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "arnie" version))
              (sha256
               (base32
                "14xkgyfn9zvkbgram15w7qzqc5pl1a8ig66cif7a79najrgd914r"))))
    (properties `((upstream-name . "arnie")))
    (build-system r-build-system)
    (home-page "https://github.com/imanuelcostigan/arnie")
    (synopsis "\"Arnie\" box office records 1982-2014")
    (description
     "Arnold Schwarzenegger movie weekend box office records from 1982-2014")
    (license license:cc-by-sa4.0)))

(define-public r-armspp
  (package
    (name "r-armspp")
    (version "0.0.2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "armspp" version))
              (sha256
               (base32
                "098c59hdzr4ly8sx72xkcbjmiz5y65id1slsscwjji1yssb23lqq"))))
    (properties `((upstream-name . "armspp")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpp))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=armspp")
    (synopsis "Adaptive Rejection Metropolis Sampling (ARMS) via 'Rcpp'")
    (description
     "An efficient Rcpp implementation of the Adaptive Rejection Metropolis Sampling
(ARMS) algorithm proposed by Gilks, W. R., Best, N. G. and Tan, K. K. C. (1995)
<doi:10.2307/2986138>.  This allows for sampling from a univariate target
probability distribution specified by its (potentially unnormalised) log
density.")
    (license license:expat)))

(define-public r-armada
  (package
    (name "r-armada")
    (version "0.1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "armada" version))
              (sha256
               (base32
                "191iwf5y1za3wssawkyi9jcingfqqxcvv88hglpw6j7y3x5f47hf"))))
    (properties `((upstream-name . "armada")))
    (build-system r-build-system)
    (propagated-inputs (list r-vsurf
                             r-qvalue
                             r-mvtnorm
                             r-impute
                             r-glmnet
                             r-famt
                             r-doparallel
                             r-complexheatmap
                             r-clustofvar
                             r-circlize
                             r-anapuce))
    (home-page "https://cran.r-project.org/package=armada")
    (synopsis
     "Statistical Methodology to Select Covariates in High-Dimensional Data under Dependence")
    (description
     "Two steps variable selection procedure in a context of high-dimensional
dependent data but few observations.  First step is dedicated to eliminate
dependence between variables (clustering of variables, followed by factor
analysis inside each cluster).  Second step is a variable selection using by
aggregation of adapted methods.  Bastien B., Chakir H., Gegout-Petit A.,
Muller-Gueudin A., Shi Y. A statistical methodology to select covariates in
high-dimensional data under dependence.  Application to the classification of
genetic profiles associated with outcome of a non-small-cell lung cancer
treatment.  2018. <https://hal.archives-ouvertes.fr/hal-01939694>.")
    (license license:gpl3)))

(define-public r-arkhe
  (package
    (name "r-arkhe")
    (version "1.0.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "arkhe" version))
              (sha256
               (base32
                "0n4l4mahblgzhmlwysvfvlx686zix718sp53irgg39553mfzqj8b"))))
    (properties `((upstream-name . "arkhe")))
    (build-system r-build-system)
    (home-page "https://packages.tesselle.org/arkhe/")
    (synopsis "Tools for Cleaning Rectangular Data")
    (description
     "This package provides a dependency-free collection of simple functions for
cleaning rectangular data.  This package allows to detect, count and replace
values or discard rows/columns using a predicate function.  In addition, it
provides tools to check conditions and return informative error messages.")
    (license license:gpl3+)))

(define-public r-arkdb
  (package
    (name "r-arkdb")
    (version "0.0.16")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "arkdb" version))
              (sha256
               (base32
                "1xzp0j20z8vbzaalmxxqdcipd5fr6syw2k96fv2i6cf54xdaa1p3"))))
    (properties `((upstream-name . "arkdb")))
    (build-system r-build-system)
    (propagated-inputs (list r-dbi))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/ropensci/arkdb")
    (synopsis "Archive and Unarchive Databases Using Flat Files")
    (description
     "Flat text files provide a robust, compressible, and portable way to store tables
from databases.  This package provides convenient functions for exporting tables
from relational database connections into compressed text files and streaming
those text files back into a database without requiring the whole table to fit
in working memory.")
    (license license:expat)))

(define-public r-arimaann
  (package
    (name "r-arimaann")
    (version "0.1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ARIMAANN" version))
              (sha256
               (base32
                "0n4n9srl56s6pxjib43ksb9rahmsb509sfvpjk4py8m4r01ab2m2"))))
    (properties `((upstream-name . "ARIMAANN")))
    (build-system r-build-system)
    (propagated-inputs (list r-tseries r-forecast))
    (home-page "https://cran.r-project.org/package=ARIMAANN")
    (synopsis "Time Series Forecasting using ARIMA-ANN Hybrid Model")
    (description
     "Testing, Implementation, and Forecasting of the ARIMA-ANN hybrid model.  The
ARIMA-ANN hybrid model combines the distinct strengths of the Auto-Regressive
Integrated Moving Average (ARIMA) model and the Artificial Neural Network (ANN)
model for time series forecasting.For method details see Zhang, GP (2003)
<doi:10.1016/S0925-2312(01)00702-0>.")
    (license license:gpl3)))

(define-public r-aribrain
  (package
    (name "r-aribrain")
    (version "0.2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ARIbrain" version))
              (sha256
               (base32
                "18c7yxkrnqh18gcfzvdc5wqig6ywdmjcy8rlz0fdj3b8fb84dfpr"))))
    (properties `((upstream-name . "ARIbrain")))
    (build-system r-build-system)
    (propagated-inputs (list r-rnifti r-plyr r-hommel))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=ARIbrain")
    (synopsis "All-Resolution Inference")
    (description
     "It performs All-Resolutions Inference (ARI) on functional Magnetic Resonance
Image (fMRI) data.  As a main feature, it estimates lower bounds for the
proportion of active voxels in a set of clusters as, for example, given by a
cluster-wise analysis.  The method is described in Rosenblatt, Finos, Weeda,
Solari, Goeman (2018) <doi:10.1016/j.neuroimage.2018.07.060>.")
    (license license:gpl2+)))

(define-public r-ari
  (package
    (name "r-ari")
    (version "0.3.5")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ari" version))
              (sha256
               (base32
                "03w99c918jp23d0kl26vx4m7xjicpgwl5rhn9d0fsm4kvv7j87li"))))
    (properties `((upstream-name . "ari")))
    (build-system r-build-system)
    (inputs (list ffmpeg))
    (propagated-inputs (list r-xml2
                             r-webshot
                             r-tuner
                             r-text2speech
                             r-rvest
                             r-rmarkdown
                             r-purrr
                             r-progress
                             r-hms))
    (native-inputs (list r-knitr))
    (home-page "http://github.com/seankross/ari")
    (synopsis "Automated R Instructor")
    (description
     "Create videos from R Markdown documents, or images and audio files.  These
images can come from image files or HTML slides, and the audio files can be
provided by the user or computer voice narration can be created using Amazon
Polly'.  The purpose of this package is to allow users to create accessible,
translatable, and reproducible lecture videos.  See
<https://aws.amazon.com/polly/> for more information.")
    (license license:expat)))

(define-public r-arht
  (package
    (name "r-arht")
    (version "0.1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ARHT" version))
              (sha256
               (base32
                "1fz81a202r8vk655dg6a03zfq3gfkimqjvmc95k3j02xz0iv58kn"))))
    (properties `((upstream-name . "ARHT")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=ARHT")
    (synopsis
     "Adaptable Regularized Hotelling's T^2 Test for High-Dimensional Data")
    (description
     "Perform the Adaptable Regularized Hotelling's T^2 test (ARHT) proposed by Li et
al., (2016) <arXiv:1609.08725>.  Both one-sample and two-sample mean test are
available with various probabilistic alternative prior models.  It contains a
function to consistently estimate higher order moments of the population
covariance spectral distribution using the spectral of the sample covariance
matrix (Bai et al. (2010) <doi:10.1111/j.1467-842X.2010.00590.x>).  In addition,
it contains a function to sample from 3-variate chi-squared random vectors
approximately with a given correlation matrix when the degrees of freedom are
large.")
    (license license:gpl2+)))

(define-public r-argus
  (package
    (name "r-argus")
    (version "0.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "argus" version))
              (sha256
               (base32
                "0k016fpz03gzsy165cqk1gbszrk7xr330hxcnjl1d5r2hnfxgvxl"))))
    (properties `((upstream-name . "argus")))
    (build-system r-build-system)
    (propagated-inputs (list r-runuran))
    (home-page "https://cran.r-project.org/package=argus")
    (synopsis "Random Variate Generator for the Argus Distribution")
    (description
     "Random variate generation, density, CDF and quantile function for the Argus
distribution.  Especially, it includes for random variate generation a flexible
inversion method that is also fast in the varying parameter case.  A
Ratio-of-Uniforms method is provided as second alternative.")
    (license license:gpl2+)))

(define-public r-argosfilter
  (package
    (name "r-argosfilter")
    (version "0.70")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "argosfilter" version))
              (sha256
               (base32
                "1cqhpq5z807azpc45d00031bhw5q69111jsblyqdp5bg6qinrj9c"))))
    (properties `((upstream-name . "argosfilter")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=argosfilter")
    (synopsis "Argos Locations Filter")
    (description
     "Filters animal satellite tracking data obtained from the Argos
system(<https://www.argos-system.org/>), following the algorithm described in
Freitas et al (2008) <doi:10.1111/j.1748-7692.2007.00180.x>.  It is especially
indicated for telemetry studies of marine animals, where Argos locations are
predominantly of low-quality.")
    (license license:gpl2+)))

(define-public r-argonr
  (package
    (name "r-argonr")
    (version "0.2.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "argonR" version))
              (sha256
               (base32
                "15hlvansqnky9bnq4r7xza3hb1hzylmhz8117wxz9lxa1wiky2is"))))
    (properties `((upstream-name . "argonR")))
    (build-system r-build-system)
    (propagated-inputs (list r-rstudioapi r-htmltools))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/RinteRface/argonR")
    (synopsis "R Interface to Argon HTML Design")
    (description "R wrapper around the argon HTML library.  More at
<https://demos.creative-tim.com/argon-design-system/>.")
    (license license:gpl2)))

(define-public r-argondash
  (package
    (name "r-argondash")
    (version "0.2.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "argonDash" version))
              (sha256
               (base32
                "1wykr7y5375g1nb18ynybccxmd948xrr0gdwxxqsfjf782vlgd2d"))))
    (properties `((upstream-name . "argonDash")))
    (build-system r-build-system)
    (propagated-inputs (list r-shiny r-htmltools r-argonr))
    (home-page "https://github.com/RinteRface/argonDash")
    (synopsis "Argon Shiny Dashboard Template")
    (description
     "Create awesome Bootstrap 4 dashboards powered by Argon'.  See more here
<https://rinterface.github.io/argonDash/>.")
    (license license:gpl2)))

(define-public r-argofloats
  (package
    (name "r-argofloats")
    (version "1.0.6")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "argoFloats" version))
              (sha256
               (base32
                "1ldnqg5zwczv3sfdy3s06gyri1a05l6qfgwab68ns0d24b69yrlk"))))
    (properties `((upstream-name . "argoFloats")))
    (build-system r-build-system)
    (propagated-inputs (list r-oce))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/ArgoCanada/argoFloats")
    (synopsis "Analysis of Oceanographic Argo Floats")
    (description
     "Supports the analysis of oceanographic data recorded by Argo autonomous drifting
profiling floats.  Functions are provided to (a) download and cache data files,
(b) subset data in various ways, (c) handle quality-control flags and (d) plot
the results according to oceanographic conventions.  A shiny app is provided for
easy exploration of datasets.  The package is designed to work well with the oce
package, providing a wide range of processing capabilities that are particular
to oceanographic analysis.  See Kelley, Harbin, and Richards (2021)
<doi:10.3389/fmars.2021.635922> for more on the scientific context and
applications.")
    (license license:gpl2+)))

(define-public r-argo
  (package
    (name "r-argo")
    (version "3.0.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "argo" version))
              (sha256
               (base32
                "1q7gbyk2f8vimwzdmd1mfqyaql2gyawywilwzs6g1716gbk3gd80"))))
    (properties `((upstream-name . "argo")))
    (build-system r-build-system)
    (propagated-inputs (list r-zoo
                             r-xts
                             r-xtable
                             r-xml
                             r-matrix
                             r-glmnet
                             r-boot))
    (home-page "https://cran.r-project.org/package=argo")
    (synopsis
     "Accurate Estimation of Influenza Epidemics using Google Search Data")
    (description
     "Augmented Regression with General Online data (ARGO) for accurate estimation of
influenza epidemics in United States on national level, regional level and state
level.  It replicates the method introduced in paper Yang, S., Santillana, M.
and Kou, S.C. (2015) <doi:10.1073/pnas.1515373112>; Ning, S., Yang, S. and Kou,
S.C. (2019) <doi:10.1038/s41598-019-41559-6>; Yang, S., Ning, S. and Kou, S.C.
(2021) <doi:10.1038/s41598-021-83084-5>.")
    (license license:gpl2)))

(define-public r-arfima
  (package
    (name "r-arfima")
    (version "1.8-1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "arfima" version))
              (sha256
               (base32
                "1msbd52989yqxqxgapgjvzfzzpkr2w9dp7ig8racqpzwqnjhpswb"))))
    (properties `((upstream-name . "arfima")))
    (build-system r-build-system)
    (propagated-inputs (list r-ltsa))
    (native-inputs (list gfortran))
    (home-page "https://cran.r-project.org/package=arfima")
    (synopsis "Fractional ARIMA (and Other Long Memory) Time Series Modeling")
    (description
     "Simulates, fits, and predicts long-memory and anti-persistent time series,
possibly mixed with ARMA, regression, transfer-function components.  Exact
methods (MLE, forecasting, simulation) are used.  Bug reports should be done via
GitHub (at <https://github.com/JQVeenstra/arfima>), where the development
version of this package lives; it can be installed using devtools.")
    (license license:expat)))

(define-public r-arenar
  (package
    (name "r-arenar")
    (version "0.2.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "arenar" version))
              (sha256
               (base32
                "08b865v7ringqzm5m4ib4nrmlyqywir6bjj7alzmg06dy7mrl9s7"))))
    (properties `((upstream-name . "arenar")))
    (build-system r-build-system)
    (propagated-inputs (list r-plumber
                             r-jsonlite
                             r-ingredients
                             r-ibreakdown
                             r-gistr
                             r-fairmodels
                             r-dalex
                             r-auditor))
    (native-inputs (list r-knitr))
    (home-page "https://arenar.drwhy.ai")
    (synopsis "Arena for the Exploration and Comparison of any ML Models")
    (description
     "Generates data for challenging machine learning models in Arena
<https://arena.drwhy.ai> - an interactive web application.  You can start the
server with XAI (Explainable Artificial Intelligence) plots to be generated
on-demand or precalculate and auto-upload data file beside shareable Arena URL.")
    (license license:gpl3)))

(define-public r-arena2r
  (package
    (name "r-arena2r")
    (version "1.0.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "arena2r" version))
              (sha256
               (base32
                "14zjpglp389pldi436935fz6mgi4jdgfii1m035nsvihrms9gqkh"))))
    (properties `((upstream-name . "arena2r")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-shinyjs
                             r-shinydashboard
                             r-shinybs
                             r-shiny
                             r-rlang
                             r-purrr
                             r-magrittr
                             r-ggplot2
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/pedroliman/arena2r")
    (synopsis "Plots, Summary Statistics and Tools for Arena Simulation Users")
    (description
     "Reads Arena <https://www.arenasimulation.com/> CSV output files and generates
nice tables and plots.  The package contains a Shiny App that can be used to
interactively visualize Arena's results.")
    (license license:expat)))

(define-public r-areaplot
  (package
    (name "r-areaplot")
    (version "1.2.3")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "areaplot" version))
              (sha256
               (base32
                "1j342mgjfxca38j4xx0bp35fjdx1xsfp1czdlpahavg5xm94lwbf"))))
    (properties `((upstream-name . "areaplot")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=areaplot")
    (synopsis "Plot Stacked Areas and Confidence Bands as Filled Polygons")
    (description
     "Plot stacked areas and confidence bands as filled polygons, or add polygons to
existing plots.  A variety of input formats are supported, including vectors,
matrices, data frames, formulas, etc.")
    (license license:gpl3)))

(define-public r-areal
  (package
    (name "r-areal")
    (version "0.1.8")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "areal" version))
              (sha256
               (base32
                "14hwif59lxjdf0crq5mp2w2rhz9b7l1b33r0ssd1j60ml2fv6488"))))
    (properties `((upstream-name . "areal")))
    (build-system r-build-system)
    (propagated-inputs (list r-sf r-rlang r-purrr r-glue r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://chris-prener.github.io/areal/")
    (synopsis "Areal Weighted Interpolation")
    (description
     "This package provides a pipeable, transparent implementation of areal weighted
interpolation with support for interpolating multiple variables in a single
function call.  These tools provide a full-featured workflow for validation and
estimation that fits into both modern data management (e.g. tidyverse) and
spatial data (e.g. sf) frameworks.")
    (license license:gpl3)))

(define-public r-areabiplot
  (package
    (name "r-areabiplot")
    (version "1.0.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "areabiplot" version))
              (sha256
               (base32
                "0izgvlg174jbr3fm3qc8zh23kfs7hn9bwd40x6vm90iivrrgdcp7"))))
    (properties `((upstream-name . "areabiplot")))
    (build-system r-build-system)
    (propagated-inputs (list r-nipals))
    (home-page "https://cran.r-project.org/package=areabiplot")
    (synopsis "Area Biplot")
    (description
     "Considering an (n x m) data matrix X, this package is based on the method
proposed by Gower, Groener, and Velden (2010) <doi:10.1198/jcgs.2010.07134>, and
utilize the resulting matrices from the extended version of the NIPALS
decomposition to determine n triangles whose areas are used to visually estimate
the elements of a specific column of X. After a 90-degree rotation of the sample
points, the triangles are drawn regarding the following points: 1.the origin of
the axes; 2.the sample points; 3.  the vector endpoint representing some
variable.")
    (license license:expat)))

(define-public r-ardl-nardl
  (package
    (name "r-ardl-nardl")
    (version "1.2.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ardl.nardl" version))
              (sha256
               (base32
                "1ylciaxq218j28zjrmlmj43sz7hz2zvjgfrm72ijdqqj133z9g9r"))))
    (properties `((upstream-name . "ardl.nardl")))
    (build-system r-build-system)
    (propagated-inputs (list r-tseries
                             r-texreg
                             r-stringr
                             r-sandwich
                             r-rlist
                             r-nardl
                             r-lmtest
                             r-gets
                             r-dplyr
                             r-car))
    (home-page "https://cran.r-project.org/package=ardl.nardl")
    (synopsis
     "Linear and Nonlinear Autoregressive Distributed Lag Models: General-to-Specific Approach")
    (description
     "Estimate the linear and nonlinear autoregressive distributed lag (ARDL & NARDL)
models and the corresponding error correction models, and test for longrun and
short-run asymmetric.  The general-to-specific approach is also available in
estimating the ARDL and NARDL models.  The Pesaran, Shin & Smith (2001)
(<doi:10.1002/jae.616>) bounds test for level relationships is also provided.
The ardl.nardl package also performs short-run and longrun symmetric
restrictions available at Shin et al. (2014) <doi:10.1007/978-1-4899-8008-3_9>
and their corresponding tests.")
    (license license:gpl2+)))

(define-public r-ardl
  (package
    (name "r-ardl")
    (version "0.2.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ARDL" version))
              (sha256
               (base32
                "151mw6z67ssa3pykmbcijgcw4msbrpn1l4b5qj3pz9v9k3j05idl"))))
    (properties `((upstream-name . "ARDL")))
    (build-system r-build-system)
    (propagated-inputs (list r-zoo
                             r-stringr
                             r-msm
                             r-lmtest
                             r-dynlm
                             r-dplyr
                             r-aod))
    (home-page "https://github.com/Natsiopoulos/ARDL")
    (synopsis "ARDL, ECM and Bounds-Test for Cointegration")
    (description
     "This package creates complex autoregressive distributed lag (ARDL) models and
constructs the underlying unrestricted and restricted error correction model
(ECM) automatically, just by providing the order.  It also performs the
bounds-test for cointegration as described in Pesaran et al. (2001)
<doi:10.1002/jae.616> and provides the multipliers and the cointegrating
equation.  The validity and the accuracy of this package have been verified by
successfully replicating the results of Pesaran et al. (2001) in Natsiopoulos
and Tzeremes (2022) <doi:10.1002/jae.2919>.")
    (license license:gpl3)))

(define-public r-ardec
  (package
    (name "r-ardec")
    (version "2.1-1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ArDec" version))
              (sha256
               (base32
                "17k2lnvh6vf9gy2xmyncriyjxy37ih7plvslld37kbrwh8dhybx0"))))
    (properties `((upstream-name . "ArDec")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=ArDec")
    (synopsis "Time Series Autoregressive-Based Decomposition")
    (description
     "Autoregressive-based decomposition of a time series based on the approach in
West (1997).  Particular cases include the extraction of trend and seasonal
components.")
    (license license:gpl2+)))

(define-public r-arctools
  (package
    (name "r-arctools")
    (version "1.1.6")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "arctools" version))
              (sha256
               (base32
                "01a1kmkmnwm8ryv1hr0w79ghbk844w7fnv1yiq9mmwrs4jbgfrcf"))))
    (properties `((upstream-name . "arctools")))
    (build-system r-build-system)
    (propagated-inputs (list r-runstats r-lubridate))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=arctools")
    (synopsis
     "Processing and Physical Activity Summaries of Minute Level Activity Data")
    (description
     "This package provides functions to process minute level actigraphy-measured
activity counts data and extract commonly used physical activity volume and
fragmentation metrics.")
    (license license:gpl3)))

(define-public r-arcpullr
  (package
    (name "r-arcpullr")
    (version "0.2.7")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "arcpullr" version))
              (sha256
               (base32
                "1nbz5br6vm0ka9jn2cnkf2g90l6d0pzvma2x5dlq5arpg5jmca4b"))))
    (properties `((upstream-name . "arcpullr")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-sf
                             r-rlang
                             r-rgdal
                             r-raster
                             r-jsonlite
                             r-httr
                             r-ggplot2
                             r-dt
                             r-dplyr
                             r-bslib))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=arcpullr")
    (synopsis "Pull Data from an 'ArcGIS REST' API")
    (description
     "This package provides functions to efficiently query ArcGIS REST APIs
<https://developers.arcgis.com/rest/>.  Both spatial and SQL queries can be used
to retrieve data.  Simple Feature (sf) objects are utilized to perform spatial
queries.  This package was neither produced nor is maintained by Esri.")
    (license license:gpl3)))

(define-public r-arcokrig
  (package
    (name "r-arcokrig")
    (version "0.1.2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ARCokrig" version))
              (sha256
               (base32
                "0pk0y0gsw681py0vwizxvh1jqjnapzqfr0mbdpli1sray55xbjr2"))))
    (properties `((upstream-name . "ARCokrig")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcppeigen r-rcpparmadillo r-rcpp r-mvtnorm
                             r-ggplot2))
    (home-page "https://CRAN.R-project.org/package=ARCokrig")
    (synopsis "Autoregressive Cokriging Models for Multifidelity Codes")
    (description
     "For emulating multifidelity computer models.  The major methods include
univariate autoregressive cokriging and multivariate autoregressive cokriging.
The autoregressive cokriging methods are implemented for both hierarchically
nested design and non-nested design.  For hierarchically nested design, the
model parameters are estimated via standard optimization algorithms; For
non-nested design, the model parameters are estimated via Monte Carlo
expectation-maximization (MCEM) algorithms.  In both cases, the priors are
chosen such that the posterior distributions are proper.  Notice that the
uniform priors on range parameters in the correlation function lead to improper
posteriors.  This should be avoided when Bayesian analysis is adopted.  The
development of objective priors for autoregressive cokriging models can be found
in Pulong Ma (2020) <DOI:10.1137/19M1289893>.  The development of the
multivariate autoregressive cokriging models with possibly non-nested design can
be found in Pulong Ma, Georgios Karagiannis, Bledar A Konomi, Taylor G Asher,
Gabriel R Toro, and Andrew T Cox (2019) <arXiv:1909.01836>.")
    (license license:gpl2+)))

(define-public r-arco
  (package
    (name "r-arco")
    (version "0.3-1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ArCo" version))
              (sha256
               (base32
                "1afjdmcalx3m19jlvqs83fg5qlds59l5zzg3pzk13qk31r0hz7mk"))))
    (properties `((upstream-name . "ArCo")))
    (build-system r-build-system)
    (propagated-inputs (list r-matrix r-glmnet r-boot))
    (home-page "https://cran.r-project.org/package=ArCo")
    (synopsis "Artificial Counterfactual Package")
    (description
     "Set of functions to analyse and estimate Artificial Counterfactual models from
Carvalho, Masini and Medeiros (2016) <DOI:10.2139/ssrn.2823687>.")
    (license license:expat)))

(define-public r-archivist-github
  (package
    (name "r-archivist-github")
    (version "0.2.6")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "archivist.github" version))
              (sha256
               (base32
                "092fzi505vx9xbk41m86d0isxna42iflp7q2kjiqa6z1ccvim2yx"))))
    (properties `((upstream-name . "archivist.github")))
    (build-system r-build-system)
    (propagated-inputs (list r-jsonlite r-httr r-git2r r-digest r-archivist))
    (native-inputs (list r-knitr))
    (home-page "http://marcinkosinski.github.io/archivist.github/")
    (synopsis "Tools for Archiving, Managing and Sharing R Objects via GitHub")
    (description
     "The extension of the archivist package integrating the archivist with GitHub via
GitHub API, git2r packages and httr package.")
    (license license:gpl2)))

(define-public r-archiveretriever
  (package
    (name "r-archiveretriever")
    (version "0.2.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "archiveRetriever" version))
              (sha256
               (base32
                "0m6f0a5ymwmxwa43rh06hw49dl1dilk20lskrsgcfmkq2hy6wr7i"))))
    (properties `((upstream-name . "archiveRetriever")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml2
                             r-tidyr
                             r-tibble
                             r-stringr
                             r-rvest
                             r-lubridate
                             r-jsonlite
                             r-httr
                             r-gridextra
                             r-ggplot2
                             r-dplyr
                             r-anytime))
    (home-page "https://github.com/liserman/archiveRetriever/")
    (synopsis "Retrieve Archived Web Pages from the 'Internet Archive'")
    (description
     "Scraping content from archived web pages stored in the Internet Archive
(<https://archive.org>) using a systematic workflow.  Get an overview of the
mementos available from the respective homepage, retrieve the Urls and links of
the page and finally scrape the content.  The final output is stored in tibbles,
which can be then easily used for further analysis.")
    (license (license:fsdg-compatible "Apache License (>= 2.0)"))))

(define-public r-archive
  (package
    (name "r-archive")
    (version "1.1.5")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "archive" version))
              (sha256
               (base32
                "0zq61bvma82fxvczy3bhfy3x8k5s36avmblvfl1vsa2f0rp63nmk"))))
    (properties `((upstream-name . "archive")))
    (build-system r-build-system)
    (inputs (list zlib libarchive libarchive libarchive))
    (propagated-inputs (list r-tibble r-rlang r-glue r-cpp11 r-cli))
    (native-inputs (list pkg-config))
    (home-page "https://archive.r-lib.org/")
    (synopsis "Multi-Format Archive and Compression Support")
    (description
     "Bindings to libarchive <http://www.libarchive.org> the Multi-format archive and
compression library.  Offers R connections and direct extraction for many
archive formats including tar', ZIP', 7-zip', RAR', CAB and compression formats
including gzip', bzip2', compress', lzma and xz'.")
    (license license:expat)))

(define-public r-archidart
  (package
    (name "r-archidart")
    (version "3.4")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "archiDART" version))
              (sha256
               (base32
                "1wvjlg2rwy39czf3qqh9igk9rmk9i7pxa9yl5x9yqmsagwd1av3n"))))
    (properties `((upstream-name . "archiDART")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml r-sp r-gtools r-geometry))
    (home-page "https://archidart.github.io/")
    (synopsis
     "Plant Root System Architecture Analysis Using DART and RSML Files")
    (description
     "Analysis of complex plant root system architectures (RSA) using the output files
created by Data Analysis of Root Tracings (DART), an open-access software
dedicated to the study of plant root architecture and development across time
series (Le Bot et al (2010) \"DART: a software to analyse root system
architecture and development from captured images\", Plant and Soil,
<DOI:10.1007/s11104-009-0005-2>), and RSA data encoded with the Root System
Markup Language (RSML) (Lobet et al (2015) \"Root System Markup Language: toward
a unified root architecture description language\", Plant Physiology,
<DOI:10.1104/pp.114.253625>).  More information can be found in Delory et al
(2016) \"archiDART: an R package for the automated computation of plant root
architectural traits\", Plant and Soil, <DOI:10.1007/s11104-015-2673-4>.")
    (license license:gpl2)))

(define-public r-archi
  (package
    (name "r-archi")
    (version "2.1.3")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "aRchi" version))
              (sha256
               (base32
                "0irfp76f1vkbhz60s4b3nhqk06f1z08v68qba9hfkmcra2xnqkjy"))))
    (properties `((upstream-name . "aRchi")))
    (build-system r-build-system)
    (propagated-inputs (list r-voxr
                             r-svmisc
                             r-stringr
                             r-rgl
                             r-rfast
                             r-r-matlab
                             r-progress
                             r-pracma
                             r-plyr
                             r-pkgcond
                             r-lidr
                             r-gtools
                             r-fnn
                             r-fastcluster
                             r-dplyr
                             r-dicekriging
                             r-data-table
                             r-circular))
    (home-page "https://github.com/umr-amap/aRchi")
    (synopsis
     "Quantitative Structural Model ('QSM') Treatment for Tree Architecture")
    (description
     "This package provides a set of tools to make quantitative structural model of
trees (i.e the so-called QSM') from LiDAR point cloud, to manipulate and
visualize the QSMs as well as to compute metrics from them.  It can be used in
various context of forest ecology (i.e biomass estimation) and tree architecture
(i.e architectural metrics), see Martin-Ducup et al. (2020)
<doi:10.1111/1365-2435.13678>.  The package is based on a new S4 class called
aRchi'.")
    (license license:cecill)))

(define-public r-archetyper
  (package
    (name "r-archetyper")
    (version "0.1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "archetyper" version))
              (sha256
               (base32
                "1d4vz7kj7n5j81fwfxvr47if8c7fdycci6n33wf8paac0v2paqli"))))
    (properties `((upstream-name . "archetyper")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyverse
                             r-testthat
                             r-stringr
                             r-snakecase
                             r-skimr
                             r-rmarkdown
                             r-readr
                             r-ps
                             r-log4r
                             r-knitr
                             r-here
                             r-feather
                             r-config
                             r-bannercommenter))
    (native-inputs (list r-knitr))
    (home-page "https://mkorvink.github.io/archetyper/index.html")
    (synopsis "An Archetype for Data Mining and Data Science Projects")
    (description
     "This package provides a project template to support the data science workflow.")
    (license license:gpl3+)))

(define-public r-archetypal
  (package
    (name "r-archetypal")
    (version "1.3.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "archetypal" version))
              (sha256
               (base32
                "0xih81gwfwr1x9671gpzw49v95hmnl497hahxsyvdla87n1bfpc3"))))
    (properties `((upstream-name . "archetypal")))
    (build-system r-build-system)
    (propagated-inputs (list r-plot3d
                             r-matrix
                             r-lpsolve
                             r-inflection
                             r-geometry
                             r-entropy
                             r-doparallel))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=archetypal")
    (synopsis "Finds the Archetypal Analysis of a Data Frame")
    (description
     "This package performs archetypal analysis by using Principal Convex Hull
Analysis under a full control of all algorithmic parameters.  It contains a set
of functions for determining the initial solution, the optimal algorithmic
parameters and the optimal number of archetypes.  Post run tools are also
available for the assessment of the derived solution.  Morup, M., Hansen, LK
(2012) <doi:10.1016/j.neucom.2011.06.033>.  Hochbaum, DS, Shmoys, DB (1985)
<doi:10.1287/moor.10.2.180>.  Eddy, WF (1977) <doi:10.1145/355759.355768>.
Barber, CB, Dobkin, DP, Huhdanpaa, HT (1996) <doi:10.1145/235815.235821>.
Christopoulos, DT (2016) <doi:10.2139/ssrn.3043076>.  Falk, A., Becker, A.,
Dohmen, T., Enke, B., Huffman, D., Sunde, U. (2018), <doi:10.1093/qje/qjy013>.
Christopoulos, DT (2015) <doi:10.1016/j.jastp.2015.03.009> .  Murari, A.,
Peluso, E., Cianfrani, Gaudio, F., Lungaroni, M., (2019),
<doi:10.3390/e21040394>.")
    (license license:gpl2+)))

(define-public r-archeofrag
  (package
    (name "r-archeofrag")
    (version "0.8.2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "archeofrag" version))
              (sha256
               (base32
                "1xnfb4midmjlhq2x8mv6r0mrjbm529xnfm8y0q9wll73igg696yl"))))
    (properties `((upstream-name . "archeofrag")))
    (build-system r-build-system)
    (propagated-inputs (list r-igraph))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/sebastien-plutniak/archeofrag")
    (synopsis "Refitting and Spatial Analysis in Archaeology")
    (description
     "This package provides methods to analyse fragmented objects in archaeology using
refitting relationships between fragments scattered in archaeological spatial
units (e.g. stratigraphic layers).  Graphs and graph theory are used to model
archaeological observations.  The package is mainly based on the igraph package
for graph analysis.  Functions can: 1) create, manipulate, and simulate
fragmentation graphs, 2) measure the cohesion and admixture of archaeological
spatial units, and 3) characterise the topology of a specific set of refitting
relationships.  An empirical dataset is also provided as an example.
Documentation about archeofrag is provided by the vignette included in this
package and by the accompanying scientific papers: Plutniak (2021, Journal of
Archaeological Science, <doi:10.1016/j.jas.2021.105501>) and Plutniak (2022,
Journal of Open Source Software, <doi:10.21105/joss.04335>).")
    (license license:gpl3)))

(define-public r-archdata
  (package
    (name "r-archdata")
    (version "1.2-1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "archdata" version))
              (sha256
               (base32
                "1dahfl9xdnqiwzdrff98x23k1dl19sfdqnv7jlg1xzgvhj1fhk0d"))))
    (properties `((upstream-name . "archdata")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=archdata")
    (synopsis "Example Datasets from Archaeological Research")
    (description
     "The archdata package provides several types of data that are typically used in
archaeological research.  It provides all of the data sets used in \"Quantitative
Methods in Archaeology Using R\" by David L Carlson, one of the Cambridge Manuals
in Archaeology.")
    (license license:gpl2+)))

(define-public r-archaeophases-dataset
  (package
    (name "r-archaeophases-dataset")
    (version "0.2.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ArchaeoPhases.dataset" version))
              (sha256
               (base32
                "0yffzc9jmyiil3p0bvf0fpq64mn55swcnizi3bgsl44d4j93y68q"))))
    (properties `((upstream-name . "ArchaeoPhases.dataset")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=ArchaeoPhases.dataset")
    (synopsis "Data Sets for 'ArchaeoPhases' Vignettes")
    (description
     "This package provides the data sets used to build the ArchaeoPhases vignettes.
The data sets were formerly distributed with ArchaeoPhases', however they exceed
current CRAN policy for package size.")
    (license license:gpl3)))

(define-public r-archaeophases
  (package
    (name "r-archaeophases")
    (version "1.8")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ArchaeoPhases" version))
              (sha256
               (base32
                "00d8lpasz96l55v3982mqg85b237lxvsjl65p288yzj87860v2kj"))))
    (properties `((upstream-name . "ArchaeoPhases")))
    (build-system r-build-system)
    (propagated-inputs (list r-toordinal
                             r-shiny
                             r-reshape2
                             r-readr
                             r-magrittr
                             r-hdrcde
                             r-gtools
                             r-gplots
                             r-ggraph
                             r-ggplot2
                             r-ggalt
                             r-dplyr
                             r-digest
                             r-coda))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=ArchaeoPhases")
    (synopsis
     "Post-Processing of the Markov Chain Simulated by 'ChronoModel', 'Oxcal' or 'BCal'")
    (description
     "This package provides a list of functions for the statistical analysis of
archaeological dates and groups of dates.  It is based on the post-processing of
the Markov Chains whose stationary distribution is the posterior distribution of
a series of dates.  Such output can be simulated by different applications as
for instance ChronoModel (see <https://chronomodel.com/>), Oxcal (see
<https://c14.arch.ox.ac.uk/oxcal.html>) or BCal (see
<https://bcal.shef.ac.uk/>).  The only requirement is to have a csv file
containing a sample from the posterior distribution.  Note that this package
interacts with data available through the ArchaeoPhases.dataset package which is
available in a separate repository.  The size of the ArchaeoPhases.dataset
package is approximately 4 MB.")
    (license license:gpl3)))

(define-public r-archaeochron
  (package
    (name "r-archaeochron")
    (version "0.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ArchaeoChron" version))
              (sha256
               (base32
                "1qma2432mm73h72g9ah1k02wlcb6yrhc6mpai9nj7v58s126ffxn"))))
    (properties `((upstream-name . "ArchaeoChron")))
    (build-system r-build-system)
    (propagated-inputs (list r-rjags r-coda r-bchron r-archaeophases))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=ArchaeoChron")
    (synopsis "Bayesian Modeling of Archaeological Chronologies")
    (description
     "This package provides a list of functions for the Bayesian modeling of
archaeological chronologies.  The Bayesian models are implemented in JAGS ('JAGS
stands for Just Another Gibbs Sampler.  It is a program for the analysis of
Bayesian hierarchical models using Markov Chain Monte Carlo (MCMC) simulation.
See <http://mcmc-jags.sourceforge.net/> and \"JAGS Version 4.3.0 user manual\",
Martin Plummer (2017)
<https://sourceforge.net/projects/mcmc-jags/files/Manuals/>.).  The inputs are
measurements with their associated standard deviations and the study period.
The output is the MCMC sample of the posterior distribution of the event date
with or without radiocarbon calibration.")
    (license license:gpl3)))

(define-public r-arcensreg
  (package
    (name "r-arcensreg")
    (version "2.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ARCensReg" version))
              (sha256
               (base32
                "05zjk1wxqfigzg80lvx1940a059jfdr9zbzgzmz2n01glj1lvj63"))))
    (properties `((upstream-name . "ARCensReg")))
    (build-system r-build-system)
    (propagated-inputs (list r-tmvtnorm r-numderiv r-mvtnorm r-msm))
    (home-page "https://cran.r-project.org/package=ARCensReg")
    (synopsis
     "Fitting Univariate Censored Linear Regression Model with Autoregressive Errors")
    (description
     "It fits an univariate left or right censored linear regression model with
autoregressive errors under the normal distribution.  It provides estimates and
standard errors of the parameters, prediction of future observations and it
supports missing values on the dependent variable.  It also performs influence
diagnostic through local influence for three possible perturbation schemes.")
    (license license:gpl2+)))

(define-public r-arc
  (package
    (name "r-arc")
    (version "1.3")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "arc" version))
              (sha256
               (base32
                "0isfa7d26jpj004lf4f06krbfa68zyzrh5431xa63k2dykvg8c5j"))))
    (properties `((upstream-name . "arc")))
    (build-system r-build-system)
    (propagated-inputs (list r-r-utils r-matrix r-discretization r-arules))
    (home-page "https://github.com/kliegr/arc")
    (synopsis "Association Rule Classification")
    (description
     "This package implements the Classification-based on Association Rules (CBA)
(Bing Liu, Wynne Hsu,	Yiming Ma (1999)
<https://dl.acm.org/doi/10.5555/3000292.3000305>) algorithm for association rule
classification (ARC).  The package also contains several convenience methods
that allow to automatically set CBA parameters (minimum confidence, minimum
support) and it also natively handles numeric attributes by integrating a
pre-discretization step.  The rule generation phase is handled by the arules
package.  To further decrease the size of the CBA models produced by the arc
package, postprocessing by the qCBA package is suggested.  QCBA package can be
obtained from CRAN archive or from <https://github.com/kliegr/QCBA>.")
    (license license:agpl3)))

(define-public r-ararredux
  (package
    (name "r-ararredux")
    (version "1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ArArRedux" version))
              (sha256
               (base32
                "11h88gnj54cn5fbxf163s8kjqc1q452nzb218fjlwsxxwzaz5gbr"))))
    (properties `((upstream-name . "ArArRedux")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=ArArRedux")
    (synopsis
     "Rigorous Data Reduction and Error Propagation of Ar40 / Ar39 Data")
    (description
     "Processes noble gas mass spectrometer data to determine the isotopic composition
of argon (comprised of Ar36, Ar37, Ar38, Ar39 and Ar40) released from
neutron-irradiated potassium-bearing minerals.  Then uses these compositions to
calculate precise and accurate geochronological ages for multiple samples as
well as the covariances between them.  Error propagation is done in matrix form,
which jointly treats all samples and all isotopes simultaneously at every step
of the data reduction process.  Includes methods for regression of the
time-resolved mass spectrometer signals to t=0 ('time zero') for both single-
and multi-collector instruments, blank correction, mass fractionation
correction, detector intercalibration, decay corrections, interference
corrections, interpolation of the irradiation parameter between neutron fluence
monitors, and (weighted mean) age calculation.  All operations are performed on
the logs of the ratios between the different argon isotopes so as to properly
treat them as compositional data', sensu Aitchison [1986, The Statistics of
Compositional Data, Chapman and Hall].")
    (license license:gpl2)))

(define-public r-arakno
  (package
    (name "r-arakno")
    (version "1.3.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "arakno" version))
              (sha256
               (base32
                "1mbbb4bzcck78wma9nrmpava81cii92rzjq0yl3p38zvnym2i2m9"))))
    (properties `((upstream-name . "arakno")))
    (build-system r-build-system)
    (propagated-inputs (list r-rworldxtra
                             r-rworldmap
                             r-rgbif
                             r-phytools
                             r-jsonlite
                             r-httr
                             r-ape))
    (home-page "https://cran.r-project.org/package=arakno")
    (synopsis "ARAchnid KNowledge Online")
    (description
     "Allows the user to connect with the World Spider Catalogue (WSC;
<https://wsc.nmbe.ch/>) and the World Spider Trait (WST;
<https://spidertraits.sci.muni.cz/>) databases.  Also performs several basic
functions such as checking names validity, retrieving coordinate data from the
Global Biodiversity Information Facility (GBIF; <https://www.gbif.org/>), and
mapping.")
    (license license:gpl3)))

(define-public r-arabicstemr
  (package
    (name "r-arabicstemr")
    (version "1.3")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "arabicStemR" version))
              (sha256
               (base32
                "1ak57zci3ckfmpdmgw8hadnfg81hxp69h21s6a3ad3yldvcqg010"))))
    (properties `((upstream-name . "arabicStemR")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=arabicStemR")
    (synopsis "Arabic Stemmer for Text Analysis")
    (description "Allows users to stem Arabic texts for text analysis.")
    (license license:gpl2+)))

(define-public r-arabic2kansuji
  (package
    (name "r-arabic2kansuji")
    (version "0.1.3")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "arabic2kansuji" version))
              (sha256
               (base32
                "1f8ca7hwbn3vl44xrvpfb5n11rv4sbhv2ksg88kx7rk7hik5rbdi"))))
    (properties `((upstream-name . "arabic2kansuji")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr r-purrr))
    (home-page "https://github.com/indenkun/arabic2kansuji")
    (synopsis "Convert Arabic Numerals to Kansuji")
    (description
     "Simple functions to convert given Arabic numerals to Kansuji numerical figures
that represent numbers written in Chinese characters.")
    (license license:expat)))

(define-public r-ar-matrix
  (package
    (name "r-ar-matrix")
    (version "0.1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ar.matrix" version))
              (sha256
               (base32
                "1d531hkl50szfa1q0zbp8dp1a9jli63kwvxjgc9n0ar279y47qdz"))))
    (properties `((upstream-name . "ar.matrix")))
    (build-system r-build-system)
    (propagated-inputs (list r-sparsemvn r-sp r-matrix r-mass))
    (home-page "https://cran.r-project.org/package=ar.matrix")
    (synopsis "Simulate Auto Regressive Data from Precision Matricies")
    (description
     "Using sparse precision matricies and Choleski factorization simulates data that
is auto-regressive.")
    (license license:gpl2+)))

(define-public r-ar
  (package
    (name "r-ar")
    (version "1.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AR" version))
              (sha256
               (base32
                "1wn4g2997c4vc3mzq2pv8ld0ryp0i78v4zlqqryvhshxgnz4f2pr"))))
    (properties `((upstream-name . "AR")))
    (build-system r-build-system)
    (propagated-inputs (list r-distrib))
    (home-page "https://cran.r-project.org/package=AR")
    (synopsis "Another Look at the Acceptance-Rejection Method")
    (description
     "In mathematics, rejection sampling is a basic technique used to generate
observations from a distribution.  It is also commonly called the
Acceptance-Rejection method or Accept-Reject algorithm and is a type of Monte
Carlo method.  Acceptance-Rejection method is based on the observation that to
sample a random variable one can perform a uniformly random sampling of the 2D
cartesian graph, and keep the samples in the region under the graph of its
density function.  Package AR is able to generate/simulate random data from a
probability density function by Acceptance-Rejection method.  Moreover, this
package is a useful teaching resource for graphical presentation of
Acceptance-Rejection method.  From the practical point of view, the user needs
to calculate a constant in Acceptance-Rejection method, which package AR is able
to compute this constant by optimization tools.  Several numerical examples are
provided to illustrate the graphical presentation for the Acceptance-Rejection
Method.")
    (license license:lgpl3+)))

(define-public r-aquodom
  (package
    (name "r-aquodom")
    (version "0.1.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "aquodom" version))
              (sha256
               (base32
                "11w3qf1fwa5gqbiwfq23hrw8k009xbn8rwdb5fgckykyc49lhqbk"))))
    (properties `((upstream-name . "aquodom")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble
                             r-stringr
                             r-rlang
                             r-readr
                             r-openxlsx
                             r-memoise
                             r-magrittr
                             r-lubridate
                             r-httr
                             r-glue
                             r-dplyr
                             r-cachem))
    (home-page "https://redtent.github.io/aquodom/")
    (synopsis "Access to Aquo domaintables from R (Dutch)")
    (description
     "The Aquo Standard is the Dutch Standard for the exchange of data in water
management.  With *aquodom* (short for aquo domaintables) it is easy to exploit
the API (<https://www.aquo.nl/index.php/Hoofdpagina>) to download domaintables
of the Aquo Standard and use them in R.")
    (license license:expat)))

(define-public r-aquaenv
  (package
    (name "r-aquaenv")
    (version "1.0-4")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AquaEnv" version))
              (sha256
               (base32
                "07yx7mbslqgqg7ky67n3xfhskaj7s3w5mvl7xkih48xbsdlmxi4l"))))
    (properties `((upstream-name . "AquaEnv")))
    (build-system r-build-system)
    (propagated-inputs (list r-minpack-lm))
    (home-page "https://cran.r-project.org/package=AquaEnv")
    (synopsis
     "Integrated Development Toolbox for Aquatic Chemical Model Generation")
    (description
     "Toolbox for the experimental aquatic chemist, focused on acidification and CO2
air-water exchange.  It contains all elements to model the pH, the related CO2
air-water exchange, and aquatic acid-base chemistry for an arbitrary marine,
estuarine or freshwater system.  It contains a suite of tools for sensitivity
analysis, visualisation, modelling of chemical batches, and can be used to build
dynamic models of aquatic systems.  As from version 1.0-4, it also contains
functions to calculate the buffer factors.")
    (license license:gpl2+)))

(define-public r-aquadtree
  (package
    (name "r-aquadtree")
    (version "1.0.2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AQuadtree" version))
              (sha256
               (base32
                "1nq2k8dkviazh09pglgla7vgvxwgckkbwx20rs8q9k0xnmsz86yz"))))
    (properties `((upstream-name . "AQuadtree")))
    (build-system r-build-system)
    (propagated-inputs (list r-sp r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=AQuadtree")
    (synopsis "Confidentiality of Spatial Point Data")
    (description
     "This package provides an automatic aggregation tool to manage point data
privacy, intended to be helpful for the production of official spatial data and
for researchers.  The package pursues the data accuracy at the smallest possible
areas preventing individual information disclosure.  The methodology, based on
hierarchical geographic data structures performs aggregation and local
suppression of point data to ensure privacy as described in Lagonigro, R.,
Oller, R., Martori J.C. (2017) <doi:10.2436/20.8080.02.55>.  The data structures
are created following the guidelines for grid datasets from the European Forum
for Geography and Statistics.")
    (license license:expat)))

(define-public r-aquabpsim
  (package
    (name "r-aquabpsim")
    (version "0.0.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AquaBPsim" version))
              (sha256
               (base32
                "0bf83kp8j7il5q9kr8r0pxlnsf6l9nvhgkny4y5wgc8pbki0dsmz"))))
    (properties `((upstream-name . "AquaBPsim")))
    (build-system r-build-system)
    (propagated-inputs (list r-readxl r-pedigree r-matlib r-mass))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=AquaBPsim")
    (synopsis "Aquaculture Breeding Program Simulation")
    (description
     "Breeding programs can be simulated with this package.  The functions are written
to simulate production and reproduction systems encountered in aquaculture and
are easy to combine with custom functions.  Simulating breeding programs is
useful to predict the expected genetic gain, rate of inbreeding and the effect
of changes in the breeding program.  AquaBPsim does not simulate genome
wide-markers and QTLs, but it simulates estimated breeding values as values
correlated to the true breeding values.  The correlation equals the accuracy,
which can be provided or calculated using deterministic formulas.  For genomic
selection, the accuracy can be calculate using the formula of Deatwyler et al.
(2010) <doi:10.1534/genetics.110.116855>.  Without genomic selection, accuracy
can be calculated with the selection index method (Mrode, 2014.
ISBN:978-1-84593-981-6).")
    (license license:expat)))

(define-public r-aqp
  (package
    (name "r-aqp")
    (version "1.42")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "aqp" version))
              (sha256
               (base32
                "06mgrxq2kq5qkg5sqxvvllk1iwd28p2j82m9fr4cjv2icklll3fl"))))
    (properties `((upstream-name . "aqp")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr
                             r-sp
                             r-plyr
                             r-lattice
                             r-data-table
                             r-cluster))
    (home-page "https://github.com/ncss-tech/aqp")
    (synopsis "Algorithms for Quantitative Pedology")
    (description
     "The Algorithms for Quantitative Pedology (AQP) project was started in 2009 to
organize a loosely-related set of concepts and source code on the topic of soil
profile visualization, aggregation, and classification into this package (aqp).
Over the past 8 years, the project has grown into a suite of related R packages
that enhance and simplify the quantitative analysis of soil profile data.
Central to the AQP project is a new vocabulary of specialized functions and data
structures that can accommodate the inherent complexity of soil profile
information; freeing the scientist to focus on ideas rather than boilerplate
data processing tasks <doi:10.1016/j.cageo.2012.10.020>.  These functions and
data structures have been extensively tested and documented, applied to projects
involving hundreds of thousands of soil profiles, and deeply integrated into
widely used tools such as SoilWeb
<https://casoilresource.lawr.ucdavis.edu/soilweb-apps/>.  Components of the AQP
project (aqp, soilDB, sharpshootR, soilReports packages) serve an important role
in routine data analysis within the USDA-NRCS Soil Science Division.  The AQP
suite of R packages offer a convenient platform for bridging the gap between
pedometric theory and practice.")
    (license license:gpl3+)))

(define-public r-aqlschemes
  (package
    (name "r-aqlschemes")
    (version "1.7-1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AQLSchemes" version))
              (sha256
               (base32
                "10j8qh7m975666ipgdvzrjiraqqb5rn8qj4w76s3ijl83y0v5j3v"))))
    (properties `((upstream-name . "AQLSchemes")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=AQLSchemes")
    (synopsis "Retrieving Acceptance Sampling Schemes")
    (description
     "This package provides functions are included for recalling AQL (Acceptable
Quality Level or Acceptance Quality Level) Based single, double, and multiple
attribute sampling plans from the Military Standard (MIL-STD-105E) - American
National Standards Institute/American Society for Quality (ANSI/ASQ Z1.4) tables
and for retrieving variable sampling plans from Military Standard (MIL-STD-414)
- American National Standards Institute/American Society for Quality (ANSI/ASQ
Z1.9) tables.  The sources for these tables are listed in the URL: field.  Also
included are functions for computing the OC (Operating Characteristic) and ASN
(Average Sample Number) coordinates for the attribute plans it recalls, and
functions for computing the estimated proportion nonconforming and the maximum
allowable proportion nonconforming for variable sampling plans.  The MIL-STD AQL
Sampling schemes were the most used and copied set of standards in the world.
They are intended to be used for sampling a stream of lots, and were used in
contract agreements between supplier and customer companies.  When the US
military dropped support of MIL-STD 105E and 414, The American National
Standards Institute (ANSI) and the International Standards Organization (ISO)
adopted the standard with few changes or no changes to the central tables.  This
package is useful because its computer implementation of these tables duplicates
that available in other commercial software and subscription online calculators.")
    (license license:gpl2)))

(define-public r-aqeval
  (package
    (name "r-aqeval")
    (version "0.4.5")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AQEval" version))
              (sha256
               (base32
                "14i731bdr6yrdgl9zqlyw46yd5mnj0q3sqmqfqxcvs39lxkvm473"))))
    (properties `((upstream-name . "AQEval")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-strucchange
                             r-segmented
                             r-purrr
                             r-openair
                             r-mgcv
                             r-lubridate
                             r-loa
                             r-ggtext
                             r-ggplot2
                             r-dplyr))
    (home-page "https://github.com/karlropkins/AQEval")
    (synopsis "Air Quality Evaluation")
    (description
     "Developed for use by those tasked with the routine detection, characterisation
and quantification of discrete changes in air quality time-series, such as
identifying the impacts of air quality policy interventions.  The main functions
use signal isolation then break-point/segment (BP/S) methods based on
strucchange and segmented methods detect and quantify change events (Ropkins &
Tate, 2021, <doi:10.1016/j.scitotenv.2020.142374>).")
    (license license:gpl3+)))

(define-public r-apyramid
  (package
    (name "r-apyramid")
    (version "0.1.2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "apyramid" version))
              (sha256
               (base32
                "0ws6dfd6v3p9rhpmf06786yl2gaw1h2n1d76a054iap8bvgyahzw"))))
    (properties `((upstream-name . "apyramid")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyselect
                             r-scales
                             r-rlang
                             r-glue
                             r-ggplot2
                             r-forcats
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/R4EPI/apyramid")
    (synopsis "Visualize Population Pyramids Aggregated by Age")
    (description
     "This package provides a quick method for visualizing non-aggregated line-list or
aggregated census data stratified by age and one or two categorical variables
(e.g. gender and health status) with any number of values.  It returns a ggplot
object, allowing the user to further customize the output.  This package is part
of the R4Epis project <https://r4epis.netlify.com>.")
    (license license:gpl3)))

(define-public r-aptreeshape
  (package
    (name "r-aptreeshape")
    (version "1.5-0.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "apTreeshape" version))
              (sha256
               (base32
                "1wxhfp21ir9yv4wnbh7ay2x05k822nsyd5smlxmk67wm5w4vr1v1"))))
    (properties `((upstream-name . "apTreeshape")))
    (build-system r-build-system)
    (propagated-inputs (list r-quantreg r-pbapply r-cubature r-coda r-ape))
    (home-page "https://cran.r-project.org/package=apTreeshape")
    (synopsis "Analyses of Phylogenetic Treeshape")
    (description
     "Simulation and analysis of phylogenetic tree topologies using statistical
indices.  It is a companion library of the ape package.  It provides additional
functions for reading, plotting, manipulating phylogenetic trees.  It also
offers convenient web-access to public databases, and enables testing null
models of macroevolution using corrected test statistics.  Trees of class
\"phylo\" (from ape package) can be converted easily.  Implements methods
described in Bortolussi et al. (2005) <doi:10.1093/bioinformatics/bti798> and
Maliet et al. (2017) <doi:10.1101/224295>.")
    (license license:gpl2+)))

(define-public r-aptools
  (package
    (name "r-aptools")
    (version "6.8.8")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "APtools" version))
              (sha256
               (base32
                "171aydyd7s8qll7djl4ysy596wxdf5wfwpqwfi14jjglc9r9qrrr"))))
    (properties `((upstream-name . "APtools")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival r-cmprsk))
    (home-page "https://cran.r-project.org/package=APtools")
    (synopsis
     "Average Positive Predictive Values (AP) for Binary Outcomes and Censored Event Times")
    (description
     "We provide tools to estimate two prediction accuracy metrics, the average
positive predictive values (AP) as well as the well-known AUC (the area under
the receiver operator characteristic curve) for risk scores.  The outcome of
interest is either binary or censored event time.  Note that for censored event
time, our functions estimates, the AP and the AUC, are time-dependent for
pre-specified time interval(s).  A function that compares the APs of two risk
scores/markers is also included.  Optional outputs include positive predictive
values and true positive fractions at the specified marker cut-off values, and a
plot of the time-dependent AP versus time (available for event time data).")
    (license license:lgpl3)))

(define-public r-apt
  (package
    (name "r-apt")
    (version "3.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "apt" version))
              (sha256
               (base32
                "14njvpf6q34nffm3r9gqcszlabzbydsxqj0ln9nk4mv59izp8sqm"))))
    (properties `((upstream-name . "apt")))
    (build-system r-build-system)
    (propagated-inputs (list r-urca r-erer r-car))
    (home-page "https://cran.r-project.org/package=apt")
    (synopsis "Asymmetric Price Transmission")
    (description
     "Asymmetric price transmission between two time series is assessed.  Several
functions are available for linear and nonlinear threshold cointegration, and
furthermore, symmetric and asymmetric error correction model.")
    (license (list license:gpl2+ license:gpl3+))))

(define-public r-apsimx
  (package
    (name "r-apsimx")
    (version "2.3.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "apsimx" version))
              (sha256
               (base32
                "1d1ipzf9ahdb3540zjcyzj4dwx5v8b73av790ahhbmc128vdmspj"))))
    (properties `((upstream-name . "apsimx")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml2 r-rsqlite r-knitr r-jsonlite r-dbi))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=apsimx")
    (synopsis
     "Inspect, Read, Edit and Run 'APSIM' \"Next Generation\" and 'APSIM' Classic")
    (description
     "The functions in this package inspect, read, edit and run files for APSIM \"Next
Generation\" ('JSON') and APSIM \"Classic\" ('XML').  The files with an apsim
extension correspond to APSIM Classic (7.x) - Windows only - and the ones with
an apsimx extension correspond to APSIM \"Next Generation\".  For more information
about APSIM see (<https://www.apsim.info/>) and for APSIM next generation
(<https://apsimnextgeneration.netlify.app/>).")
    (license license:gpl3)))

(define-public r-aprof
  (package
    (name "r-aprof")
    (version "0.4.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "aprof" version))
              (sha256
               (base32
                "14qclp88j4ygd4vrxxpgy2s9939wcajjsqycdzpvn64ws29sdpvh"))))
    (properties `((upstream-name . "aprof")))
    (build-system r-build-system)
    (propagated-inputs (list r-testthat))
    (home-page "http://github.com/MarcoDVisser/aprof")
    (synopsis "Amdahl's Profiler, Directed Optimization Made Easy")
    (description
     "Assists the evaluation of whether and where to focus code optimization, using
Amdahl's law and visual aids based on line profiling.  Amdahl's profiler
organizes profiling output files (including memory profiling) in a visually
appealing way.  It is meant to help to balance development vs. execution time by
helping to identify the most promising sections of code to optimize and
projecting potential gains.  The package is an addition to R's standard
profiling tools and is not a wrapper for them.")
    (license license:gpl2+)))

(define-public r-aprean3
  (package
    (name "r-aprean3")
    (version "1.0.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "aprean3" version))
              (sha256
               (base32
                "17rnq02sncl6rzwyln10200s43b8z1s2j0kdi9kgcb6qr51v12rv"))))
    (properties `((upstream-name . "aprean3")))
    (build-system r-build-system)
    (home-page "https://github.com/lbraglia/aprean3")
    (synopsis
     "Datasets from Draper and Smith \"Applied Regression Analysis\" (3rd Ed., 1998)")
    (description
     "An unofficial companion to the textbook \"Applied Regression Analysis\" by N.R.
Draper and H. Smith (3rd Ed., 1998) including all the accompanying datasets.")
    (license license:gpl3)))

(define-public r-approxot
  (package
    (name "r-approxot")
    (version "1.0.2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "approxOT" version))
              (sha256
               (base32
                "1j17dcs4nxss81q1d3mf6h7nkzrq202n7pqb7phza085xmjvpksx"))))
    (properties `((upstream-name . "approxOT")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcppeigen r-rcppcgal r-rcpp r-bh))
    (home-page "https://cran.r-project.org/package=approxOT")
    (synopsis "Approximate and Exact Optimal Transport Methods")
    (description
     "R and C++ functions to perform exact and approximate optimal transport.  All C++
methods are linkable to other R packages via their header files.")
    (license license:gpl3+)))

(define-public r-approxmatch
  (package
    (name "r-approxmatch")
    (version "2.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "approxmatch" version))
              (sha256
               (base32
                "1n6v1h4zf1nf8j1a5d0h95v6q8dff39v9061i7zzi9ci3lw04748"))))
    (properties `((upstream-name . "approxmatch")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=approxmatch")
    (synopsis
     "Approximately Optimal Fine Balance Matching with Multiple Groups")
    (description
     "Tools for constructing a matched design with multiple comparison groups.
Further specifications of refined covariate balance restriction and exact match
on covariate can be imposed.  Matches are approximately optimal in the sense
that the cost of the solution is at most twice the optimal cost, Crama and
Spieksma (1992) <doi:10.1016/0377-2217(92)90078-N>, Karmakar, Small and
Rosenbaum (2019) <doi:10.1080/10618600.2019.1584900>.")
    (license license:expat)))

(define-public r-approximator
  (package
    (name "r-approximator")
    (version "1.2-7")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "approximator" version))
              (sha256
               (base32
                "0smqjdla9mvzy164nsb0pw0sgal3w2wnyhqidp74h0smyczrr1zw"))))
    (properties `((upstream-name . "approximator")))
    (build-system r-build-system)
    (propagated-inputs (list r-mvtnorm r-emulator))
    (home-page "https://cran.r-project.org/package=approximator")
    (synopsis "Bayesian Prediction of Complex Computer Codes")
    (description
     "This package performs Bayesian prediction of complex computer codes when fast
approximations are available.  It uses a hierarchical version of the Gaussian
process, originally proposed by Kennedy and O'Hagan (2000), Biometrika 87(1):1.")
    (license license:gpl2)))

(define-public r-appnn
  (package
    (name "r-appnn")
    (version "1.0-0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "appnn" version))
              (sha256
               (base32
                "0wkpr6lcd68wlzk6n622ab7sd99l837073czn4k56hw8bw9v68j3"))))
    (properties `((upstream-name . "appnn")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=appnn")
    (synopsis "Amyloid Propensity Prediction Neural Network")
    (description
     "Amyloid propensity prediction neural network (APPNN) is an amyloidogenicity
propensity predictor based on a machine learning approach through recursive
feature selection and feed-forward neural networks, taking advantage of newly
published sequences with experimental, in vitro, evidence of amyloid formation.")
    (license license:gpl3)))

(define-public r-appliedpredictivemodeling
  (package
    (name "r-appliedpredictivemodeling")
    (version "1.1-7")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AppliedPredictiveModeling" version))
              (sha256
               (base32
                "1wi0sw5w1c51rmh9z98wdpk5rgzsylkkb6g019djiwxvj92l99hh"))))
    (properties `((upstream-name . "AppliedPredictiveModeling")))
    (build-system r-build-system)
    (propagated-inputs (list r-reshape2
                             r-plyr
                             r-mass
                             r-lattice
                             r-ellipse
                             r-corelearn))
    (home-page "http://appliedpredictivemodeling.com/")
    (synopsis "Functions and Data Sets for 'Applied Predictive Modeling'")
    (description
     "This package provides a few functions and several data set for the Springer book
Applied Predictive Modeling'.")
    (license license:gpl2)))

(define-public r-applicable
  (package
    (name "r-applicable")
    (version "0.1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "applicable" version))
              (sha256
               (base32
                "1n81aa5by0fd47wjksdl0zpzf0w4vgrns6iqv5i9lqs7g64zggs0"))))
    (properties `((upstream-name . "applicable")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyselect
                             r-tidyr
                             r-tibble
                             r-rlang
                             r-purrr
                             r-proxyc
                             r-matrix
                             r-hardhat
                             r-glue
                             r-ggplot2
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/tidymodels/applicable")
    (synopsis "Compilation of Applicability Domain Methods")
    (description
     "This package provides a modeling package compiling applicability domain methods
in R. It combines different methods to measure the amount of extrapolation new
samples can have from the training set.  See Gadaleta et al (2016)
<doi:10.4018/IJQSPR.2016010102> for an overview of applicability domains.")
    (license license:expat)))

(define-public r-appler
  (package
    (name "r-appler")
    (version "0.1.4")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "appler" version))
              (sha256
               (base32
                "0a3xhr2zbzni81y00sa1d35spcd1f6blhnkmyf76wf00z3vhrk2i"))))
    (properties `((upstream-name . "appler")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml2 r-rvest r-jsonlite r-httr r-glue))
    (home-page "https://github.com/ashbaldry/appler")
    (synopsis "'Apple App Store' and 'iTunes' Data Extraction")
    (description
     "Using Apple App Store <https://www.apple.com/app-store/> web scraping and iTunes
API
<https://performance-partners.apple.com/resources/documentation/itunes-store-web-service-search-api.html>
to extract content information, app ratings and reviews.")
    (license license:gpl2)))

(define-public r-appleadsr
  (package
    (name "r-appleadsr")
    (version "0.1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "appleadsR" version))
              (sha256
               (base32
                "19xkzykk6zdbswdkfix9nqnfgab4r9c21rqwpma1r6fjapsp81jf"))))
    (properties `((upstream-name . "appleadsR")))
    (build-system r-build-system)
    (propagated-inputs (list r-jsonlite))
    (native-inputs (list r-knitr))
    (home-page "https://windsor.ai/")
    (synopsis "Get Apple Search Ads Data via the 'Windsor.ai' API")
    (description
     "Collect your data on digital marketing campaigns from Apple Search Ads using the
Windsor.ai API <https://windsor.ai/api-fields/>.")
    (license license:gpl3)))

(define-public r-appestimation
  (package
    (name "r-appestimation")
    (version "0.1.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "APPEstimation" version))
              (sha256
               (base32
                "1bg9ma4i3k3xdgyk2h4f368gqnczvlhvjw4114iznmrv1wl4g25c"))))
    (properties `((upstream-name . "APPEstimation")))
    (build-system r-build-system)
    (propagated-inputs (list r-densratio))
    (home-page "https://cran.r-project.org/package=APPEstimation")
    (synopsis "Adjusted Prediction Model Performance Estimation")
    (description
     "Calculating predictive model performance measures adjusted for predictor
distributions using density ratio method (Sugiyama et al., (2012,
ISBN:9781139035613)).  L1 and L2 error for continuous outcome and C-statistics
for binomial outcome are computed.")
    (license license:gpl2)))

(define-public r-apollo
  (package
    (name "r-apollo")
    (version "0.2.8")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "apollo" version))
              (sha256
               (base32
                "129qa303fckan6n8zdgsa08720aiyv623rz5mdv4l2by53i7lb2s"))))
    (properties `((upstream-name . "apollo")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble
                             r-stringr
                             r-rsghb
                             r-rcppeigen
                             r-rcpparmadillo
                             r-rcpp
                             r-randtoolbox
                             r-numderiv
                             r-mvtnorm
                             r-mnormt
                             r-maxlik
                             r-matrixstats
                             r-deriv
                             r-coda))
    (native-inputs (list r-knitr))
    (home-page "http://www.apolloChoiceModelling.com")
    (synopsis "Tools for Choice Model Estimation and Application")
    (description
     "Choice models are a widely used technique across numerous scientific
disciplines.  The Apollo package is a very flexible tool for the estimation and
application of choice models in R. Users are able to write their own model
functions or use a mix of already available ones.  Random heterogeneity, both
continuous and discrete and at the level of individuals and choices, can be
incorporated for all models.  There is support for both standalone models and
hybrid model structures.  Both classical and Bayesian estimation is available,
and multiple discrete continuous models are covered in addition to discrete
choice.  Multi-threading processing is supported for estimation and a large
number of pre and post-estimation routines, including for computing posterior
(individual-level) distributions are available.  For examples, a manual, and a
support forum, visit <http://www.ApolloChoiceModelling.com>.  For more
information on choice models see Train, K. (2009) <isbn:978-0-521-74738-7> and
Hess, S. & Daly, A.J. (2014) <isbn:978-1-781-00314-5> for an overview of the
field.")
    (license license:gpl2)))

(define-public r-apng
  (package
    (name "r-apng")
    (version "1.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "apng" version))
              (sha256
               (base32
                "0g1rs8wdcbqhyjis2r1a4d96jf0486ncnap97yjv08nk574d42wp"))))
    (properties `((upstream-name . "apng")))
    (build-system r-build-system)
    (propagated-inputs (list r-bitops))
    (home-page "https://cran.r-project.org/package=apng")
    (synopsis "Convert Png Files into Animated Png")
    (description
     "Convert several png files into an animated png file.  This package exports only
a single function `apng'.  Call the apng function with a vector of file names
(which should be png files) to convert them to a single animated png file.")
    (license (list license:gpl3
                   (license:fsdg-compatible "file://LICENSE")))))

(define-public r-apml0
  (package
    (name "r-apml0")
    (version "0.10")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "APML0" version))
              (sha256
               (base32
                "1l6mw1mqb7qnsvfv9w6yydqjsrwrsrqx3bpifyp43cf2q71yx5gp"))))
    (properties `((upstream-name . "APML0")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcppeigen r-rcpp r-matrix))
    (home-page "https://cran.r-project.org/package=APML0")
    (synopsis "Augmented and Penalized Minimization Method L0")
    (description
     "Fit linear, logistic and Cox models regularized with L0, lasso (L1), elastic-net
(L1 and L2), or net (L1 and Laplacian) penalty, and their adaptive forms, such
as adaptive lasso / elastic-net and net adjusting for signs of linked
coefficients.  It solves L0 penalty problem by simultaneously selecting
regularization parameters and performing hard-thresholding or selecting number
of non-zeros.  This augmented and penalized minimization method provides an
approximation solution to the L0 penalty problem, but runs as fast as L1
regularization problem.  The package uses one-step coordinate descent algorithm
and runs extremely fast by taking into account the sparsity structure of
coefficients.  It could deal with very high dimensional data and has superior
selection performance.")
    (license license:gpl2+)))

(define-public r-aplpack
  (package
    (name "r-aplpack")
    (version "1.3.5")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "aplpack" version))
              (sha256
               (base32
                "0kv6sbw8832hlfc6164bfvg1ga4hkfw4c7i11dlz7mbhrw2vqm24"))))
    (properties `((upstream-name . "aplpack")))
    (build-system r-build-system)
    (home-page
     "https://www.uni-bielefeld.de/fakultaeten/wirtschaftswissenschaften/fakultaet/lehrende-ehemalige/pwolf/wolf_aplpack/index.xml")
    (synopsis
     "Another Plot Package: 'Bagplots', 'Iconplots', 'Summaryplots', Slider Functions and Others")
    (description
     "Some functions for drawing some special plots: The function bagplot plots a
bagplot, faces plots chernoff faces, iconplot plots a representation of a
frequency table or a data matrix, plothulls plots hulls of a bivariate data set,
plotsummary plots a graphical summary of a data set, puticon adds icons to a
plot, skyline.hist combines several histograms of a one dimensional data set in
one plot, slider functions supports some interactive graphics, spin3R helps an
inspection of a 3-dim point cloud, stem.leaf plots a stem and leaf plot,
stem.leaf.backback plots back-to-back versions of stem and leaf plot.")
    (license license:gpl2+)))

(define-public r-aplore3
  (package
    (name "r-aplore3")
    (version "0.9")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "aplore3" version))
              (sha256
               (base32
                "0af6klscsxvh4amp519b6r41bzysf61p040fj4l5706bbya1arhw"))))
    (properties `((upstream-name . "aplore3")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://github.com/lbraglia/aplore3")
    (synopsis
     "Datasets from Hosmer, Lemeshow and Sturdivant, \"Applied Logistic Regression\" (3rd Ed., 2013)")
    (description
     "An unofficial companion to \"Applied Logistic Regression\" by D.W. Hosmer, S.
Lemeshow and R.X. Sturdivant (3rd ed., 2013) containing the dataset used in the
book.")
    (license license:gpl3)))

(define-public r-apisensr
  (package
    (name "r-apisensr")
    (version "0.3.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "apisensr" version))
              (sha256
               (base32
                "1mis266s4m0hp34m7b7p008dvw7780r8rypgbpk7h5hgd1w5d7m0"))))
    (properties `((upstream-name . "apisensr")))
    (build-system r-build-system)
    (propagated-inputs (list r-shinymaterial
                             r-shinyjs
                             r-shiny
                             r-rmarkdown
                             r-rhandsontable
                             r-igraph
                             r-htmltools
                             r-golem
                             r-glue
                             r-ggraph
                             r-ggplot2
                             r-episensr
                             r-config))
    (home-page "https://github.com/dhaine/apisensr")
    (synopsis
     "Interface to 'episensr' for Sensitivity Analysis of Epidemiological Results")
    (description
     "API for using episensr', Basic sensitivity analysis of the observed relative
risks adjusting for unmeasured confounding and misclassification of the
exposure/outcome, or both.  See <https://cran.r-project.org/package=episensr>.")
    (license license:gpl2)))

(define-public r-apis
  (package
    (name "r-apis")
    (version "1.0.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "APIS" version))
              (sha256
               (base32
                "1af82mixamllly7v1jfvn1anpm1pafkv5mshwp6nmc27vaq201z5"))))
    (properties `((upstream-name . "APIS")))
    (build-system r-build-system)
    (propagated-inputs (list r-gridextra r-ggplot2 r-foreach r-doparallel))
    (native-inputs (list r-knitr gfortran))
    (home-page "https://cran.r-project.org/package=APIS")
    (synopsis
     "Auto-Adaptive Parentage Inference Software Tolerant to Missing Parents")
    (description
     "Parentage assignment package.  Parentage assignment is performed based on
observed average Mendelian transmission probability distributions.  The main
function of this package is the function APIS(), which is the parentage
assignment function.")
    (license (list license:gpl2+ license:gpl3+))))

(define-public r-api2lm
  (package
    (name "r-api2lm")
    (version "0.1.4")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "api2lm" version))
              (sha256
               (base32
                "1hxamdf1332z8gfp5crvjhl26v9g3ibsg68vm0pas2aprh18rpjs"))))
    (properties `((upstream-name . "api2lm")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=api2lm")
    (synopsis
     "Functions and Data Sets for the Book \"A Progressive Introduction to Linear Models\"")
    (description
     "Simplifies aspects of linear regression analysis, particularly simultaneous
inference.  Additionally, supports \"A Progressive Introduction to Linear Models\"
by Joshua French (<https://jfrench.github.io/LinearRegression/>).")
    (license license:gpl3)))

(define-public r-aphylo
  (package
    (name "r-aphylo")
    (version "0.2-1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "aphylo" version))
              (sha256
               (base32
                "0kvxz5r1z63610k127ji7dangrq7pd0zfgf5yqsvn0v7j4c9c5v5"))))
    (properties `((upstream-name . "aphylo")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml2
                             r-rcpp
                             r-matrix
                             r-mass
                             r-fmcmc
                             r-coda
                             r-ape))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/USCbiostats/aphylo")
    (synopsis
     "Statistical Inference and Prediction of Annotations in Phylogenetic Trees")
    (description
     "This package implements a parsimonious evolutionary model to analyze and predict
gene-functional annotations in phylogenetic trees as described in Vega Yon et
al. (2021) <doi:10.1371/journal.pcbi.1007948>.  With a focus on computational
efficiency, aphylo makes it possible to estimate pooled phylogenetic models,
including thousands (hundreds) of annotations (trees) in the same run.  The
package also provides the tools for visualization of annotated phylogenies,
calculation of posterior probabilities (prediction,) and goodness-of-fit
assessment featured in Vega Yon et al. (2021).")
    (license license:expat)))

(define-public r-aphid
  (package
    (name "r-aphid")
    (version "1.3.3")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "aphid" version))
              (sha256
               (base32
                "1jqpn7w5sgy4k49qd9ci6yj89s55gzwl5w5ldw793mzpg6if7lfn"))))
    (properties `((upstream-name . "aphid")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpp r-openssl r-kmer))
    (native-inputs (list r-knitr))
    (home-page "http://github.com/shaunpwilkinson/aphid")
    (synopsis "Analysis with Profile Hidden Markov Models")
    (description
     "Designed for the development and application of hidden Markov models and profile
HMMs for biological sequence analysis.  Contains functions for multiple and
pairwise sequence alignment, model construction and parameter optimization, file
import/export, implementation of the forward, backward and Viterbi algorithms
for conditional sequence probabilities, tree-based sequence weighting, and
sequence simulation.  Features a wide variety of potential applications
including database searching, gene-finding and annotation, phylogenetic analysis
and sequence classification.  Based on the models and algorithms described in
Durbin et al (1998, ISBN: 9780521629713).")
    (license license:gpl3)))

(define-public r-apfun
  (package
    (name "r-apfun")
    (version "0.1.6")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "APfun" version))
              (sha256
               (base32
                "0j54pcjzr5f8xhvp41vrl0i1hchphnij6p87j16rawp21apvnxyd"))))
    (properties `((upstream-name . "APfun")))
    (build-system r-build-system)
    (propagated-inputs (list r-withr r-sp r-rgdal r-raster r-maptools))
    (home-page "https://cran.r-project.org/package=APfun")
    (synopsis "Geo-Processing Helper Functions")
    (description
     "Helper tools for facilitating basic geo-processing tasks, such as
reading/writing Shapefiles, merging polygons or generating terrain contours.")
    (license license:gpl3+)))

(define-public r-apfr
  (package
    (name "r-apfr")
    (version "1.0.2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "APFr" version))
              (sha256
               (base32
                "1vax7rfccds6qz3bi6n1h3nzl9jnxpwk331wmpsbqlk23md3m4g4"))))
    (properties `((upstream-name . "APFr")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=APFr")
    (synopsis
     "Multiple Testing Approach using Average Power Function (APF) and Bayes FDR Robust Estimation")
    (description
     "This package implements a multiple testing approach to the choice of a threshold
gamma on the p-values using the Average Power Function (APF) and Bayes False
Discovery Rate (FDR) robust estimation.  Function apf_fdr() estimates both
quantities from either raw data or p-values.  Function apf_plot() produces
smooth graphs and tables of the relevant results.  Details of the methods can be
found in Quatto P, Margaritella N, et al. (2019) <doi:10.1177/0962280219844288>.")
    (license license:gpl3)))

(define-public r-apexcharter
  (package
    (name "r-apexcharter")
    (version "0.3.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "apexcharter" version))
              (sha256
               (base32
                "1kvlsnsvgiz3akcqpiyxin264qpjbz3m8g98jgfwyiqkjhqs441a"))))
    (properties `((upstream-name . "apexcharter")))
    (build-system r-build-system)
    (propagated-inputs (list r-shiny
                             r-rlang
                             r-magrittr
                             r-jsonlite
                             r-htmlwidgets
                             r-htmltools
                             r-ggplot2))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/dreamRs/apexcharter")
    (synopsis
     "Create Interactive Chart with the JavaScript 'ApexCharts' Library")
    (description
     "This package provides an htmlwidgets interface to apexcharts.js'.  Apexcharts is
a modern JavaScript charting library to build interactive charts and
visualizations with simple API. Apexcharts examples and documentation are
available here: <https://apexcharts.com/>.")
    (license license:expat)))

(define-public r-apex
  (package
    (name "r-apex")
    (version "1.0.4")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "apex" version))
              (sha256
               (base32
                "1ddzbzpnc17yvbl5yfyp0widqlx48qwlh80xcmyzhv045s680rdk"))))
    (properties `((upstream-name . "apex")))
    (build-system r-build-system)
    (propagated-inputs (list r-phangorn r-ape r-adegenet))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/thibautjombart/apex")
    (synopsis "Phylogenetic Methods for Multiple Gene Data")
    (description
     "Toolkit for the analysis of multiple gene data (Jombart et al.  2017)
<doi:10.1111/1755-0998.12567>.  Apex implements the new S4 classes multidna',
multiphyDat and associated methods to handle aligned DNA sequences from multiple
genes.")
    (license license:gpl2+)))

(define-public r-apercu
  (package
    (name "r-apercu")
    (version "0.2.4")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "apercu" version))
              (sha256
               (base32
                "046gf4dzypl6mmq7xqkyrdasq9rsjxzsii7w4nxkbn4c40kh7bf7"))))
    (properties `((upstream-name . "apercu")))
    (build-system r-build-system)
    (propagated-inputs (list r-pls))
    (home-page "https://cran.r-project.org/package=apercu")
    (synopsis "Quick Look at your Data")
    (description
     "The goal is to print an \"aperçu\", a short view of a vector, a matrix, a
data.frame, a list or an array.  By default, it prints the first 5 elements of
each dimension.  By default, the number of columns is equal to the number of
lines.  If you want to control the selection of the elements, you can pass a
list, with each element being a vector giving the selection for each dimension.")
    (license license:cc-by-sa4.0)))

(define-public r-apdesign
  (package
    (name "r-apdesign")
    (version "1.0.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "apdesign" version))
              (sha256
               (base32
                "041zyd7ih9nnj92jj9vb9ya1ij9lmj1dzx64q74vyiadw1ix5l66"))))
    (properties `((upstream-name . "apdesign")))
    (build-system r-build-system)
    (propagated-inputs (list r-matrix))
    (home-page "https://cran.r-project.org/package=apdesign")
    (synopsis "An Implementation of the Additive Polynomial Design Matrix")
    (description
     "An implementation of the additive polynomial (AP) design matrix.  It constructs
and appends an AP design matrix to a data frame for use with longitudinal data
subject to seasonality.")
    (license license:gpl3)))

(define-public r-apctools
  (package
    (name "r-apctools")
    (version "1.0.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "APCtools" version))
              (sha256
               (base32
                "1aq55a3glsqyp7gzly1nfaxxlyiq2ki6h9i5qwgz7dbni4vwggd4"))))
    (properties `((upstream-name . "APCtools")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-scales
                             r-mgcv
                             r-knitr
                             r-ggpubr
                             r-ggplot2
                             r-dplyr
                             r-colorspace
                             r-checkmate))
    (native-inputs (list r-knitr))
    (home-page "https://bauer-alex.github.io/APCtools/")
    (synopsis "Routines for Descriptive and Model-Based APC Analysis")
    (description
     "Age-Period-Cohort (APC) analyses are used to differentiate relevant drivers for
long-term developments.  The APCtools package offers visualization techniques
and general routines to simplify the workflow of an APC analysis.  Sophisticated
functions are available both for descriptive and regression model-based
analyses.  For the former, we use density (or ridgeline) matrices and
(hexagonally binned) heatmaps as innovative visualization techniques building on
the concept of Lexis diagrams.  Model-based analyses build on the separation of
the temporal dimensions based on generalized additive models, where a tensor
product interaction surface (usually between age and period) is utilized to
represent the third dimension (usually cohort) on its diagonal.  Such tensor
product surfaces can also be estimated while accounting for further covariates
in the regression model.  See Weigert et al. (2021)
<doi:10.1177/1354816620987198> for methodological details.")
    (license license:expat)))

(define-public r-apcoa
  (package
    (name "r-apcoa")
    (version "1.3")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "aPCoA" version))
              (sha256
               (base32
                "0ybp7jd1q0md4wbal5cmcl6hg3c1wkdz5mi1w5qddgi472vv1z83"))))
    (properties `((upstream-name . "aPCoA")))
    (build-system r-build-system)
    (propagated-inputs (list r-vegan r-randomcolor r-cluster r-car r-ape))
    (home-page "https://cran.r-project.org/package=aPCoA")
    (synopsis "Covariate Adjusted PCoA Plot")
    (description
     "In fields such as ecology, microbiology, and genomics, non-Euclidean distances
are widely applied to describe pairwise dissimilarity between samples.  Given
these pairwise distances, principal coordinates analysis (PCoA) is commonly used
to construct a visualization of the data.  However, confounding covariates can
make patterns related to the scientific question of interest difficult to
observe.  We provide aPCoA as an easy-to-use tool to improve data visualization
in this context, enabling enhanced presentation of the effects of interest.
Details are described in Yushu Shi, Liangliang Zhang, Kim-Anh Do, Christine
Peterson and Robert Jenq (2020) Bioinformatics, Volume 36, Issue 13, 4099-4101.")
    (license license:gpl2+)))

(define-public r-apci
  (package
    (name "r-apci")
    (version "1.0.6")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "APCI" version))
              (sha256
               (base32
                "0lfbx067vqh2yn15jmiicva8h38k0vgdr3s6m2jgswfbp11a8pjh"))))
    (properties `((upstream-name . "APCI")))
    (build-system r-build-system)
    (propagated-inputs (list r-survey
                             r-stringr
                             r-magrittr
                             r-ggpubr
                             r-ggplot2
                             r-gee
                             r-dplyr
                             r-data-table))
    (home-page "https://cran.r-project.org/package=APCI")
    (synopsis
     "New Age-Period-Cohort Model for Describing and Investigating Inter-Cohort Differences and Life Course Dynamics")
    (description
     "It implemented Age-Period-Interaction Model (APC-I Model) proposed in the paper
of Liying Luo and James S. Hodges in 2019.  A new age-period-cohort model for
describing and investigating inter-cohort differences and life course dynamics.")
    (license license:gpl2)))

(define-public r-apcf
  (package
    (name "r-apcf")
    (version "0.3.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "apcf" version))
              (sha256
               (base32
                "194w409gz052a8gcsdn3v68sqjcwrhb1ck712nljd0iy1mgdz6cs"))))
    (properties `((upstream-name . "apcf")))
    (build-system r-build-system)
    (inputs (list geos))
    (propagated-inputs (list r-wk r-rcpp))
    (native-inputs (list r-knitr))
    (home-page "https://rnuske.github.io/apcf/")
    (synopsis "Adapted Pair Correlation Function")
    (description
     "The adapted pair correlation function transfers the concept of the pair
correlation function from point patterns to patterns of objects of finite size
and irregular shape (e.g. lakes within a country).  The pair correlation
function describes the spatial distribution of objects, e.g. random, aggregated
or regularly spaced.  This is a reimplementation of the method suggested by
Nuske et al. (2009) <doi:10.1016/j.foreco.2009.09.050> using the library GEOS'.")
    (license license:gpl3+)))

(define-public r-apcanalysis
  (package
    (name "r-apcanalysis")
    (version "1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "APCanalysis" version))
              (sha256
               (base32
                "11snn5i8zyjpzf58ica762fpp14v7x5h8a8iwx4s4v81pgvlx862"))))
    (properties `((upstream-name . "APCanalysis")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=APCanalysis")
    (synopsis
     "Analysis of Unreplicated Orthogonal Experiments using All Possible Comparisons")
    (description
     "Analysis of data from unreplicated orthogonal experiments such as 2-level
factorial and fractional factorial designs and Plackett-Burman designs using the
all possible comparisons (APC) methodology developed by Miller (2005)
<doi:10.1198/004017004000000608>.")
    (license license:gpl3)))

(define-public r-apc
  (package
    (name "r-apc")
    (version "2.0.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "apc" version))
              (sha256
               (base32
                "0vh6iyxm46k8sfa1xgz0y6m619snnm8s072kml5qgiiw5s7bqnpq"))))
    (properties `((upstream-name . "apc")))
    (build-system r-build-system)
    (propagated-inputs (list r-survey
                             r-reshape
                             r-plyr
                             r-plm
                             r-lmtest
                             r-lattice
                             r-islr
                             r-ggplot2
                             r-chainladder
                             r-car
                             r-aer))
    (home-page "https://cran.r-project.org/package=apc")
    (synopsis "Age-Period-Cohort Analysis")
    (description
     "This package provides functions for age-period-cohort analysis.  Aggregate data
can be organised in matrices indexed by age-cohort, age-period or cohort-period.
 The data can include dose and response or just doses.  The statistical model is
a generalized linear model (GLM) allowing for 3,2,1 or 0 of the
age-period-cohort factors.  Individual-level data should have a row for each
individual and columns for each of age, period, and cohort.  The statistical
model for repeated cross-section is a generalized linear model.  The statistical
model for panel data is ordinary least squares.  The canonical parametrisation
of Kuang, Nielsen and Nielsen (2008) <DOI:10.1093/biomet/asn026> is used.  Thus,
the analysis does not rely on ad hoc identification.")
    (license license:gpl3)))

(define-public r-apatree
  (package
    (name "r-apatree")
    (version "1.0.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "APAtree" version))
              (sha256
               (base32
                "0vhvx2xp62avyq405jqn4i3z8awlifcs1lb527brxxhybrhnk4rv"))))
    (properties `((upstream-name . "APAtree")))
    (build-system r-build-system)
    (propagated-inputs (list r-units
                             r-sf
                             r-rcpp
                             r-raster
                             r-lwgeom
                             r-fd
                             r-bh))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/JonasGlatthorn/APAtree/")
    (synopsis "Computation of the 'Area Potentially Available' (APA) to Trees")
    (description
     "Maps of the area potentially available (APA) of trees is calculated from mapped
forest stands using the approach from Gspaltl et al. (2012)
<doi:10.1093/forestry/cps052>.  This is done by computing a rasterized version
of weighted voronoi diagrams using a an approximation of the trees competitive
ability (e.g., crown radius, leaf area) as weight.  The main output are
Raster*'- objects from the raster package that are stored together with the raw
data in apa_list's, the main class of the APAtree package.  Aggregation
functions are provided to calculate stand characteristics based on APA-maps such
as relative proportions according to APA-size and the neighborhood diversity
index NDiv (Glatthorn (2021) <doi:10.1016/j.ecolind.2021.108073>).")
    (license license:gpl2+)))

(define-public r-apatext
  (package
    (name "r-apatext")
    (version "0.1.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "apaText" version))
              (sha256
               (base32
                "1r217k60w027i63nbj24b1rm37m4qf7a6iirc941s945babkxcmb"))))
    (properties `((upstream-name . "apaText")))
    (build-system r-build-system)
    (propagated-inputs (list r-dplyr))
    (home-page "https://cran.r-project.org/package=apaText")
    (synopsis
     "Create R Markdown Text for Results in the Style of the American Psychological Association (APA)")
    (description
     "Create APA style text from analyses for use within R Markdown documents.
Descriptive statistics, confidence intervals, and cell sizes are reported.")
    (license (license:fsdg-compatible "MIT License + file LICENSE"))))

(define-public r-apatables
  (package
    (name "r-apatables")
    (version "2.0.8")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "apaTables" version))
              (sha256
               (base32
                "0jy6x0z9ivqqkjihqhyg3fxyghqa9gs6q2bpxzjdnbcb3kq151vd"))))
    (properties `((upstream-name . "apaTables")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble
                             r-mbess
                             r-dplyr
                             r-car
                             r-broom
                             r-boot))
    (home-page "https://github.com/dstanley4/apaTables")
    (synopsis "Create American Psychological Association (APA) Style Tables")
    (description
     "This package provides a common task faced by researchers is the creation of APA
style (i.e., American Psychological Association style) tables from statistical
output.  In R a large number of function calls are often needed to obtain all of
the desired information for a single APA style table.  As well, the process of
manually creating APA style tables in a word processor is prone to transcription
errors.  This package creates Word files (.doc files) containing APA style
tables for several types of analyses.  Using this package minimizes
transcription errors and reduces the number commands needed by the user.")
    (license (license:fsdg-compatible "MIT License + file LICENSE"))))

(define-public r-apachelogprocessor
  (package
    (name "r-apachelogprocessor")
    (version "0.2.3")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ApacheLogProcessor" version))
              (sha256
               (base32
                "0h4snigh1yhp34vw52h4b6qbh9c4cvwz2cx8fwvbnw6lslmg5cgv"))))
    (properties `((upstream-name . "ApacheLogProcessor")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr r-foreach r-doparallel))
    (home-page "https://github.com/diogosmendonca/ApacheLogProcessor")
    (synopsis "Process the Apache Web Server Log Files")
    (description
     "This package provides capabilities to process Apache HTTPD Log files.The main
functionalities are to extract data from access and error log files to data
frames.")
    (license (list license:lgpl3
                   (license:fsdg-compatible "file://LICENSE")))))

(define-public r-apache-sedona
  (package
    (name "r-apache-sedona")
    (version "1.3.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "apache.sedona" version))
              (sha256
               (base32
                "0d9l0n0qnjx42ia53s9fss856iz9caxaa876ccbcaxavh7l7km56"))))
    (properties `((upstream-name . "apache.sedona")))
    (build-system r-build-system)
    (propagated-inputs (list r-sparklyr r-rlang r-dplyr r-dbplyr))
    (home-page "https://cran.r-project.org/package=apache.sedona")
    (synopsis "R Interface for Apache Sedona")
    (description
     "R interface for Apache Sedona based on sparklyr (<https://sedona.apache.org>).")
    (license license:asl2.0)))

(define-public r-apa
  (package
    (name "r-apa")
    (version "0.3.3")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "apa" version))
              (sha256
               (base32
                "1nvhl5fqramsdrkpl1nmgr1vmki5c1lkdi1kkx7ihf0cz35f7c2a"))))
    (properties `((upstream-name . "apa")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble
                             r-stringr
                             r-rmarkdown
                             r-purrr
                             r-mbess
                             r-magrittr
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/dgromer/apa")
    (synopsis
     "Format Outputs of Statistical Tests According to APA Guidelines")
    (description
     "Formatter functions in the apa package take the return value of a statistical
test function, e.g. a call to chisq.test() and return a string formatted
according to the guidelines of the APA (American Psychological Association).")
    (license license:gpl3+)))

(define-public r-aovbay
  (package
    (name "r-aovbay")
    (version "0.1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AovBay" version))
              (sha256
               (base32
                "110y9wbqr0m9b6wr1c5mncrdjpg247308989bswkqnim2msvnzcf"))))
    (properties `((upstream-name . "AovBay")))
    (build-system r-build-system)
    (propagated-inputs (list r-waiter
                             r-tibble
                             r-stringr
                             r-stanheaders
                             r-shinydashboardplus
                             r-shinydashboard
                             r-shinycssloaders
                             r-shiny
                             r-rstantools
                             r-rstan
                             r-reshape
                             r-rcppparallel
                             r-rcppeigen
                             r-rcpp
                             r-purrr
                             r-nortest
                             r-moments
                             r-htmltools
                             r-highcharter
                             r-dt
                             r-dplyr
                             r-car
                             r-broom
                             r-bh
                             r-bayesfactor))
    (home-page "https://cran.r-project.org/package=AovBay")
    (synopsis
     "Classic, Nonparametric and Bayesian One-Way Analysis of Variance Panel")
    (description
     "It covers various approaches to analysis of variance, provides an assumption
testing section in order to provide a decision diagram that allows selecting the
most appropriate technique.  It provides the classical analysis of variance, the
nonparametric equivalent of Kruskal Wallis, and the Bayesian approach.  These
results are shown in an interactive shiny panel, which allows modifying the
arguments of the tests, contains interactive graphics and presents automatic
conclusions depending on the tests in order to contribute to the interpretation
of these analyzes.  AovBay uses Stan and FactorBayes for Bayesian analysis and
Highcharts for interactive charts.")
    (license license:expat)))

(define-public r-aov1r
  (package
    (name "r-aov1r")
    (version "0.1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AOV1R" version))
              (sha256
               (base32
                "0dv7k0mifybkarpwqyla5j6cvw9dcch09wvdq09ra9bsf4vyk652"))))
    (properties `((upstream-name . "AOV1R")))
    (build-system r-build-system)
    (propagated-inputs (list r-purrr r-lazyeval r-data-table r-cellranger))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=AOV1R")
    (synopsis
     "Inference in the Balanced One-Way ANOVA Model with Random Factor")
    (description
     "This package provides functions to perform statistical inference in the balanced
one-way ANOVA model with a random factor: confidence intervals, prediction
interval, and Weerahandi generalized pivotal quantities.  References: Burdick &
Graybill (1992, ISBN-13: 978-0824786441); Weerahandi (1995)
<doi:10.1007/978-1-4612-0825-9>; Lin & Liao (2008)
<doi:10.1016/j.jspi.2008.01.001>.")
    (license license:gpl3)))

(define-public r-aos
  (package
    (name "r-aos")
    (version "0.1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "aos" version))
              (sha256
               (base32
                "0nkl7dkqjfp4ahwmn3vs0akx6x2brf0m5gzzzx6pf54j1qwypbhf"))))
    (properties `((upstream-name . "aos")))
    (build-system r-build-system)
    (propagated-inputs (list r-jsonlite r-htmltools))
    (home-page "https://felixluginbuhl.com/aos")
    (synopsis "Animate on Scroll Library for 'shiny'")
    (description
     "Trigger animation effects on scroll on any HTML element of shiny and rmarkdown',
such as any text or plot, thanks to the AOS Animate On Scroll jQuery library.")
    (license license:expat)))

(define-public r-aorsf
  (package
    (name "r-aorsf")
    (version "0.0.4")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "aorsf" version))
              (sha256
               (base32
                "1pq4cllksky81qw0pblygsssxmw1rarygzzkmsln9jlcjgwxvw3f"))))
    (properties `((upstream-name . "aorsf")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpparmadillo r-rcpp r-data-table r-collapse))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/ropensci/aorsf")
    (synopsis "Accelerated Oblique Random Survival Forests")
    (description
     "Fit, interpret, and make predictions with oblique random survival forests.
Oblique decision trees are notoriously slow compared to their axis based
counterparts, but aorsf runs as fast or faster than axis-based decision tree
algorithms for right-censored time-to-event outcomes.  Methods to accelerate and
interpret the oblique random survival forest are described in Jaeger et al.,
(2022) <arXiv:2208.01129>.")
    (license license:expat)))

(define-public r-aoristic
  (package
    (name "r-aoristic")
    (version "1.1.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "aoristic" version))
              (sha256
               (base32
                "1zanf21qmnjmwzzccpdm1bwnyhv9zqjirrylfwmbpkzlmvp0a4pb"))))
    (properties `((upstream-name . "aoristic")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-scales
                             r-plyr
                             r-openxlsx
                             r-lubridate
                             r-ggplot2
                             r-dplyr))
    (home-page "https://cran.r-project.org/package=aoristic")
    (synopsis "Generates Aoristic Probability Distributions")
    (description
     "It can sometimes be difficult to ascertain when some events (such as property
crime) occur because the victim is not present when the crime happens.  As a
result, police databases often record a start (or from') date and time, and an
end (or to') date and time.  The time span between these date/times can be
minutes, hours, or sometimes days, hence the term Aoristic'.  Aoristic is one of
the past tenses in Greek and represents an uncertain occurrence in time.  For
events with a location describes with either a latitude/longitude, or X,Y
coordinate pair, and a start and end date/time, this package generates an
aoristic data frame with aoristic weighted probability values for each hour of
the week, for each observation.  The coordinates are not necessary for the
program to calculate aoristic weights; however, they are part of this package
because a spatial component has been integral to aoristic analysis from the
start.  Dummy coordinates can be introduced if the user only has temporal data.
Outputs include an aoristic data frame, as well as summary graphs and displays.
For more information see: Ratcliffe, JH (2002) Aoristic signatures and the
temporal analysis of high volume crime patterns, Journal of Quantitative
Criminology.  18 (1): 23-43.  Note: This package replaces an original aoristic
package (version 0.6) by George Kikuchi that has been discontinued with his
permission.")
    (license license:gpl3)))

(define-public r-aoptbdtvc
  (package
    (name "r-aoptbdtvc")
    (version "0.0.2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "Aoptbdtvc" version))
              (sha256
               (base32
                "1bygvf8vgzz3wa4485x2xxpk784zmw1nwsjjjysm12brrldh8zzh"))))
    (properties `((upstream-name . "Aoptbdtvc")))
    (build-system r-build-system)
    (propagated-inputs (list r-mass r-lpsolve))
    (home-page "https://cran.r-project.org/package=Aoptbdtvc")
    (synopsis
     "A-Optimal Block Designs for Comparing Test Treatments with Controls")
    (description
     "This package provides a collection of functions to construct A-optimal block
designs for comparing test treatments with one or more control(s).  Mainly
A-optimal balanced treatment incomplete block designs, weighted A-optimal
balanced treatment incomplete block designs, A-optimal group divisible treatment
designs and A-optimal balanced bipartite block designs can be constructed using
the package.  The designs are constructed using algorithms based on linear
integer programming.  To the best of our knowledge, these facilities to
construct A-optimal block designs for comparing test treatments with one or more
controls are not available in the existing R packages.  For more details on
designs for tests versus control(s) comparisons, please see Hedayat, A. S. and
Majumdar, D. (1984) <doi:10.1080/00401706.1984.10487989> A-Optimal Incomplete
Block Designs for Control-Test Treatment Comparisons, Technometrics, 26, 363-370
and Mandal, B. N. , Gupta, V. K., Parsad, Rajender. (2017)
<doi:10.1080/03610926.2015.1071394> Balanced treatment incomplete block designs
through integer programming.  Communications in Statistics - Theory and Methods
46(8), 3728-3737.")
    (license license:gpl2+)))

(define-public r-aopdata
  (package
    (name "r-aopdata")
    (version "1.0.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "aopdata" version))
              (sha256
               (base32
                "11d9aipqcasrpi0fl2qnnqmg4wlsj3y9vy9cym4ka9jn2x1xxjns"))))
    (properties `((upstream-name . "aopdata")))
    (build-system r-build-system)
    (propagated-inputs (list r-sf r-httr r-data-table r-curl r-checkmate))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/ipeaGIT/aopdata")
    (synopsis "Data from the 'Access to Opportunities Project (AOP)'")
    (description
     "Download data from the Access to Opportunities Project (AOP)'.  The aopdata
package brings annual estimates of access to employment, health, education and
social assistance services by transport mode, as well as data on the spatial
distribution of population, jobs, health care, schools and social assistance
facilities at a fine spatial resolution for all cities included in the project.
More info on the AOP website <https://www.ipea.gov.br/acessooportunidades/en/>.")
    (license license:expat)))

(define-public r-aoos
  (package
    (name "r-aoos")
    (version "0.5.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "aoos" version))
              (sha256
               (base32
                "0y92vs27i0mkpjdclqzq4j9g1axkymhi3v8xp1v6hazh35yzjkfj"))))
    (properties `((upstream-name . "aoos")))
    (build-system r-build-system)
    (propagated-inputs (list r-roxygen2 r-magrittr))
    (native-inputs (list r-knitr))
    (home-page "https://wahani.github.io/aoos")
    (synopsis "Another Object Orientation System")
    (description
     "Another implementation of object-orientation in R. It provides syntactic sugar
for the S4 class system and two alternative new implementations.  One is an
experimental version built around S4 and the other one makes it more convenient
to work with lists as objects.")
    (license license:expat)))

(define-public r-aods3
  (package
    (name "r-aods3")
    (version "0.4-1.2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "aods3" version))
              (sha256
               (base32
                "0rd4xr7nwac49m8h4pr8hv79giyv2rrlnz78r7mxa6lpgkmgqp4d"))))
    (properties `((upstream-name . "aods3")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=aods3")
    (synopsis "Analysis of Overdispersed Data using S3 Methods")
    (description
     "This package provides functions to analyse overdispersed counts or proportions.
These functions should be considered as complements to more sophisticated
methods such as generalized estimating equations (GEE) or generalized linear
mixed effect models (GLMM).  aods3 is an S3 re-implementation of the deprecated
S4 package aod.")
    (license license:gpl2+)))

(define-public r-ao
  (package
    (name "r-ao")
    (version "0.2.3")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ao" version))
              (sha256
               (base32
                "165hgrxj2gsvkczb32480i31zs82c5mamvy2c47gsz777mw9sw1h"))))
    (properties `((upstream-name . "ao")))
    (build-system r-build-system)
    (propagated-inputs (list r-rlang r-optimizer r-lifecycle r-ggplot2))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/loelschlaeger/ao/")
    (synopsis "Alternating Optimization")
    (description
     "Alternating optimization of (high-dimensional) functions is an iterative
procedure for optimizing jointly over all parameters by alternately optimizing
parameter subsets.  For a reference on the method, see Bezdek and Hathaway
(2002) \"Some Notes on Alternating Optimization\" <doi:10.1007/3-540-45631-7_39>.")
    (license license:gpl3)))

(define-public r-anytime
  (package
    (name "r-anytime")
    (version "0.3.9")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "anytime" version))
              (sha256
               (base32
                "0jjpqynai5nd7mfy1smb44356f3d5bmpxhs1i9x9jw5c959c35hh"))))
    (properties `((upstream-name . "anytime")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpp r-bh))
    (home-page "http://dirk.eddelbuettel.com/code/anytime.html")
    (synopsis "Anything to 'POSIXct' or 'Date' Converter")
    (description
     "Convert input in any one of character, integer, numeric, factor, or ordered type
into POSIXct (or Date') objects, using one of a number of predefined formats,
and relying on Boost facilities for date and time parsing.")
    (license license:gpl2+)))

(define-public r-anylib
  (package
    (name "r-anylib")
    (version "1.0.5")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "anyLib" version))
              (sha256
               (base32
                "1x9x58hhkkwdskmgdjv94ynh811n9w0752hh4214adl1qpn576vm"))))
    (properties `((upstream-name . "anyLib")))
    (build-system r-build-system)
    (propagated-inputs (list r-withr r-httr r-devtools r-curl r-biocmanager))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=anyLib")
    (synopsis "Install and Load Any Package from CRAN, Bioconductor or Github")
    (description
     "Made to make your life simpler with packages, by installing and loading a list
of packages, whether they are on CRAN, Bioconductor or github.  For github, if
you do not have the full path, with the maintainer name in it (e.g.
\"achateigner/topReviGO\"), it will be able to load it but not to install it.")
    (license license:cc-by-sa4.0)))

(define-public r-anyflights
  (package
    (name "r-anyflights")
    (version "0.3.3")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "anyflights" version))
              (sha256
               (base32
                "1iwiil15zc4zq6y7ns8r6w27w75v72fm3syn46bxrspw0iy0lj3v"))))
    (properties `((upstream-name . "anyflights")))
    (build-system r-build-system)
    (propagated-inputs (list r-vroom
                             r-usethis
                             r-stringr
                             r-roxygen2
                             r-readr
                             r-purrr
                             r-progress
                             r-lubridate
                             r-httr
                             r-glue
                             r-dplyr
                             r-curl))
    (home-page "https://github.com/simonpcouch/anyflights")
    (synopsis
     "Query 'nycflights13'-Like Air Travel Data for Given Years and Airports")
    (description
     "Supplies a set of functions to query air travel data for user- specified years
and airports.  Datasets include on-time flights, airlines, airports, planes, and
weather.")
    (license license:cc0)))

(define-public r-anybadger
  (package
    (name "r-anybadger")
    (version "0.1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "anybadger" version))
              (sha256
               (base32
                "1aa09v5k5nlvhlir8saa5gnrq7cb1djbdc8y85cjgb3skay94hzv"))))
    (properties `((upstream-name . "anybadger")))
    (build-system r-build-system)
    (propagated-inputs (list r-r6 r-purrr r-magrittr r-glue r-config))
    (home-page "https://github.com/lmeninato/anybadger")
    (synopsis "Create Custom Pipeline Badges")
    (description
     "You can use this package to create custom pipeline badges in a standard svg
format.  This is useful for a company to use internally, where it may not be
possible to create badges through external providers.  This project was inspired
by the anybadge library in python.")
    (license license:expat)))

(define-public r-ants
  (package
    (name "r-ants")
    (version "0.0.16")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ANTs" version))
              (sha256
               (base32
                "1bvbr9m5fbq3x5mfn4xhfm2x7a8zs616cf02gzv65r8k9q2348ll"))))
    (properties `((upstream-name . "ANTs")))
    (build-system r-build-system)
    (propagated-inputs (list r-rstudioapi
                             r-rcppeigen
                             r-rcpparmadillo
                             r-rcpp
                             r-lme4
                             r-kendall
                             r-gtools))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=ANTs")
    (synopsis "Animal Network Toolkit Software")
    (description
     "How animals interact and develop social relationships in face of
sociodemographic and ecological pressures is of great interest.  New
methodologies, in particular Social Network Analysis (SNA), allow us to
elucidate these types of questions.  However, the different methodologies
developed to that end and the speed at which they emerge make their use
difficult.  Moreover, the lack of communication between the different software
developed to provide an answer to the same/different research questions is a
source of confusion.  The R package Animal Network Toolkit ANTs was developed
with the aim of implementing in one package the different social network
analysis techniques currently used in the study of animal social networks.
Hence, ANT is a toolkit for animal research allowing among other things to: 1)
measure global, dyadic and nodal networks metrics; 2) perform data
randomization: pre- and post-network (node and link permutations); 3) perform
statistical permutation tests as correlation test (<doi:10.2307/2332226>),
t-test (<doi:10.1037/h0041412>), General Linear Model (<doi:10.2307/2346786>),
General Linear Mixed Model (<doi:10.2307/2346786>), deletion simulation
(<doi:10.1098/rsbl.2003.0057>), Matrix TauKr correlations
(<doi:10.1016/S0022-5193(05)80036-0>).  The package is partially coded in C++
using the R package Rcpp for an optimal coding speed.  The package gives
researchers a workflow from the raw data to the achievement of statistical
analyses, allowing for a multilevel approach
(<doi:10.1007/978-3-319-47829-6_1882-1>): from the individual's position and
role within the network, to the identification of interaction patterns, and the
study of the overall network properties.  Furthermore, ANT also provides a
guideline on the SNA techniques used: 1) from the appropriate randomization
technique according to the data collected; 2) to the choice, the meaning, the
limitations and advantages of the network metrics to apply, 3) and the type of
statistical tests to run.  The ANT project is multi-collaborative, aiming to
provide access to advanced social network analysis techniques and to create new
ones that meet researchers needs in future versions.  The ANT project is
multi-collaborative, aiming to provide access to advanced social network
analysis techniques and to create new ones that meet researchers needs in future
versions.")
    (license license:gpl3+)))

(define-public r-antman
  (package
    (name "r-antman")
    (version "1.1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AntMAN" version))
              (sha256
               (base32
                "118jhjjfnp23kbkir66rdvlzsvms316zwr2r5msrjrb3nd8lz5va"))))
    (properties `((upstream-name . "AntMAN")))
    (build-system r-build-system)
    (propagated-inputs (list r-salso
                             r-rdpack
                             r-rcpparmadillo
                             r-rcpp
                             r-mvtnorm
                             r-mcclust
                             r-ggally
                             r-bayesplot))
    (home-page "https://github.com/bbodin/AntMAN")
    (synopsis "Anthology of Mixture Analysis Tools")
    (description
     "Fits finite Bayesian mixture models with a random number of components.  The
MCMC algorithm implemented is based on point processes as proposed by Argiento
and De Iorio (2019) <arXiv:1904.09733> and offers a more computationally
efficient alternative to reversible jump.  Different mixture kernels can be
specified: univariate Gaussian, multivariate Gaussian, univariate Poisson, and
multivariate Bernoulli (latent class analysis).  For the parameters
characterising the mixture kernel, we specify conjugate priors, with possibly
user specified hyper-parameters.  We allow for different choices for the prior
on the number of components: shifted Poisson, negative binomial, and point
masses (i.e.  mixtures with fixed number of components).")
    (license license:expat)))

(define-public r-antitrust
  (package
    (name "r-antitrust")
    (version "0.99.26")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "antitrust" version))
              (sha256
               (base32
                "172y87vnifxbs4n06v3qvwlxnl3fxhfp9cp1qzm4agcvqh1j7rxz"))))
    (properties `((upstream-name . "antitrust")))
    (build-system r-build-system)
    (propagated-inputs (list r-numderiv r-bb))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/luciu5/antitrust")
    (synopsis "Tools for Antitrust Practitioners")
    (description
     "This package provides a collection of tools for antitrust practitioners,
including the ability to calibrate different consumer demand systems and
simulate the effects of mergers under different competitive regimes.")
    (license license:cc0)))

(define-public r-anticlust
  (package
    (name "r-anticlust")
    (version "0.6.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "anticlust" version))
              (sha256
               (base32
                "1f06968i5hpfavcwmcqij0mb13jhp02gbkqiijilyiz2kc8p0nfc"))))
    (properties `((upstream-name . "anticlust")))
    (build-system r-build-system)
    (propagated-inputs (list r-rann r-matrix))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/m-Py/anticlust")
    (synopsis "Subset Partitioning via Anticlustering")
    (description
     "The method of anticlustering partitions a pool of elements into groups (i.e.,
anticlusters) with the goal of maximizing between-group similarity or
within-group heterogeneity.  The anticlustering approach thereby reverses the
logic of cluster analysis that strives for high within-group homogeneity and low
similarity of the different groups.  Computationally, anticlustering is
accomplished by maximizing instead of minimizing a clustering objective
function, such as the intra-cluster variance (used in k-means clustering) or the
sum of pairwise distances within clusters.  The function anticlustering()
implements exact and heuristic anticlustering algorithms as described in
Papenberg and Klau (2021; <doi:10.1037/met0000301>).  The exact algorithms
require that the GNU linear programming kit
(<https://www.gnu.org/software/glpk/glpk.html>) is available and the R package
Rglpk (<https://cran.R-project.org/package=Rglpk>) is installed.  A bicriterion
anticlustering method proposed by Brusco et al. (2020; <doi:10.1111/bmsp.12186>)
is available through the function bicriterion_anticlustering().  Some other
functions are available to solve classical clustering problems.  The function
balanced_clustering() applies a cluster analysis under size constraints, i.e.,
creates equal-sized clusters.  The function matching() can be used for
(unrestricted, bipartite, or K-partite) matching.  The function wce() can be
used optimally solve the (weighted) cluster editing problem, also known as
correlation clustering, clique partitioning problem or transitivity clustering.")
    (license license:expat)))

(define-public r-antibodytiters
  (package
    (name "r-antibodytiters")
    (version "0.1.24")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AntibodyTiters" version))
              (sha256
               (base32
                "1400n46kmaa074m6yilmkvcn83dyxk2w76x8cny1dygfzsnhhjxl"))))
    (properties `((upstream-name . "AntibodyTiters")))
    (build-system r-build-system)
    (propagated-inputs (list r-openxlsx r-desctools))
    (home-page "https://cran.r-project.org/package=AntibodyTiters")
    (synopsis "Antibody Titer Analysis of Vaccinated Patients")
    (description
     "Visualization of antibody titer scores is valuable for examination of
vaccination effects.  AntibodyTiters visualizes antibody titers of all or
selected patients.  This package also produces empty excel files in a specified
format, in which users can fill in experimental data for visualization.  Excel
files with toy data can also be produced, so that users can see how it is
visualized before obtaining real data.  The data should contain titer scores at
pre-vaccination, after-1st shot, after-2nd shot, and at least one additional
sampling points.  Patients with missing values can be included.  The first two
sampling points (pre-vaccination and after-1st shot) will be plotted discretely,
whereas those following will be plotted on a continuous time scale that starts
from the day of second shot.  Half-life of titer can also be calculated for each
pair of sampling points.")
    (license license:gpl3)))

(define-public r-anthropmmd
  (package
    (name "r-anthropmmd")
    (version "3.1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AnthropMMD" version))
              (sha256
               (base32
                "10ms5akc2r9dmcm8dd8bn7qn0bq71c270yhs61981n4mxsvgjmnr"))))
    (properties `((upstream-name . "AnthropMMD")))
    (build-system r-build-system)
    (propagated-inputs (list r-smacof r-shiny r-scatterplot3d r-plotrix))
    (native-inputs (list r-knitr))
    (home-page "https://gitlab.com/f-santos/anthropmmd/")
    (synopsis "An R Package for Smith's Mean Measure of Divergence (MMD)")
    (description
     "Offers a graphical user interface for the calculation of the mean measure of
divergence, with facilities for trait selection and graphical representations
<doi:10.1002/ajpa.23336>.")
    (license (list (license:fsdg-compatible "CeCILL-2")
                   (license:fsdg-compatible "file://LICENSE")))))

(define-public r-anthroplus
  (package
    (name "r-anthroplus")
    (version "0.9.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "anthroplus" version))
              (sha256
               (base32
                "1wnj2idgdnh2gdw34x40adijf2sxp3k72j45pqqxg4aqc1wrvvv1"))))
    (properties `((upstream-name . "anthroplus")))
    (build-system r-build-system)
    (propagated-inputs (list r-anthro))
    (home-page "https://cran.r-project.org/package=anthroplus")
    (synopsis
     "Computation of the WHO 2007 References for School-Age Children and Adolescents (5 to 19 Years)")
    (description
     "This package provides WHO 2007 References for School-age Children and
Adolescents (5 to 19 years) (z-scores) with confidence intervals and standard
errors around the prevalence estimates, taking into account complex sample
designs.  More information on the methods is available online:
<https://www.who.int/tools/growth-reference-data-for-5to19-years>.")
    (license license:gpl3+)))

(define-public r-anthro
  (package
    (name "r-anthro")
    (version "1.0.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "anthro" version))
              (sha256
               (base32
                "169h2vhdd2kxh4228lx1ab3fipixvka4686ngx6h8g15li9828s9"))))
    (properties `((upstream-name . "anthro")))
    (build-system r-build-system)
    (propagated-inputs (list r-survey))
    (home-page "https://github.com/worldhealthorganization/anthro")
    (synopsis "Computation of the WHO Child Growth Standards")
    (description
     "This package provides WHO Child Growth Standards (z-scores) with confidence
intervals and standard errors around the prevalence estimates, taking into
account complex sample designs.  More information on the methods is available
online: <https://www.who.int/tools/child-growth-standards>.")
    (license license:gpl3)))

(define-public r-antaresviz
  (package
    (name "r-antaresviz")
    (version "0.17.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "antaresViz" version))
              (sha256
               (base32
                "072nh0x0qrbi9va27r20vjzjsbjriqbzbpwc7vl40pimjd0hd2x4"))))
    (properties `((upstream-name . "antaresViz")))
    (build-system r-build-system)
    (propagated-inputs (list r-webshot
                             r-spmaps
                             r-sp
                             r-shiny
                             r-rgeos
                             r-raster
                             r-ramcharts
                             r-plotly
                             r-manipulatewidget
                             r-lubridate
                             r-leaflet-minicharts
                             r-leaflet
                             r-htmlwidgets
                             r-htmltools
                             r-geojsonio
                             r-dygraphs
                             r-data-table
                             r-assertthat
                             r-antaresread
                             r-antaresprocessing))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/rte-antares-rpackage/antaresViz")
    (synopsis "Antares Visualizations")
    (description
     "Visualize results generated by Antares, a powerful open source software
developed by RTE to simulate and study electric power systems (more information
about Antares here:
<https://github.com/AntaresSimulatorTeam/Antares_Simulator>).  This package
provides functions that create interactive charts to help Antares users visually
explore the results of their simulations.")
    (license (list license:gpl2+
                   (license:fsdg-compatible "file://LICENSE")))))

(define-public r-antaresread
  (package
    (name "r-antaresread")
    (version "2.3.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "antaresRead" version))
              (sha256
               (base32
                "1hiyjg4qa6qpyfbwlwa787sacf23z1mjaws24nj3h18zvwq2wk87"))))
    (properties `((upstream-name . "antaresRead")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr
                             r-shiny
                             r-plyr
                             r-pbapply
                             r-lubridate
                             r-jsonlite
                             r-httr
                             r-doparallel
                             r-data-table
                             r-bit64))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/rte-antares-rpackage/antaresRead")
    (synopsis
     "Import, Manipulate and Explore the Results of an 'Antares' Simulation")
    (description
     "Import, manipulate and explore results generated by Antares', a powerful open
source software developed by RTE (Réseau de Transport d’Électricité) to
simulate and study electric power systems (more information about Antares here :
<https://antares-simulator.org/>).")
    (license (list license:gpl2+
                   (license:fsdg-compatible "file://LICENSE")))))

(define-public r-antaresprocessing
  (package
    (name "r-antaresprocessing")
    (version "0.18.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "antaresProcessing" version))
              (sha256
               (base32
                "1dlq850xqh9534ws88ma3vv5r79cbabn6r6a2jmicxx116s7wjrz"))))
    (properties `((upstream-name . "antaresProcessing")))
    (build-system r-build-system)
    (propagated-inputs (list r-data-table r-antaresread))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/rte-antares-rpackage/antaresProcessing")
    (synopsis "'Antares' Results Processing")
    (description
     "Process results generated by Antares', a powerful open source software developed
by RTE (Réseau de Transport d’Électricité) to simulate and study electric
power systems (more information about Antares here:
<https://github.com/AntaresSimulatorTeam/Antares_Simulator>).  This package
provides functions to create new columns like net load, load factors, upward and
downward margins or to compute aggregated statistics like economic surpluses of
consumers, producers and sectors.")
    (license (list license:gpl2+
                   (license:fsdg-compatible "file://LICENSE")))))

(define-public r-antareseditobject
  (package
    (name "r-antareseditobject")
    (version "0.3.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "antaresEditObject" version))
              (sha256
               (base32
                "04rdq3kbliac1iaxqflf3qhh58qgl9pxb2qh44wkknb91ga0845x"))))
    (properties `((upstream-name . "antaresEditObject")))
    (build-system r-build-system)
    (propagated-inputs (list r-whisker
                             r-pbapply
                             r-doparallel
                             r-data-table
                             r-assertthat
                             r-antaresread))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/rte-antares-rpackage/antaresEditObject")
    (synopsis "Edit an 'Antares' Simulation")
    (description
     "Edit an Antares simulation before running it : create new areas, links, thermal
clusters or binding constraints or edit existing ones.  Update Antares general &
optimization settings.  Antares is an open source power system generator, more
information available here : <https://antares-simulator.org/>.")
    (license (list license:gpl2+
                   (license:fsdg-compatible "file://LICENSE")))))

(define-public r-antangiocool
  (package
    (name "r-antangiocool")
    (version "1.2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AntAngioCOOL" version))
              (sha256
               (base32
                "1krwms0y3xppc2y4m0az51wcbh4jq7mlr0jwinp66w8gh4k3qnp2"))))
    (properties `((upstream-name . "AntAngioCOOL")))
    (build-system r-build-system)
    (propagated-inputs (list r-rweka r-rpart r-rjava r-caret))
    (home-page "https://cran.r-project.org/package=AntAngioCOOL")
    (synopsis "Anti-Angiogenic Peptide Prediction")
    (description
     "Machine learning based package to predict anti-angiogenic peptides using
heterogeneous sequence descriptors.  AntAngioCOOL exploits five descriptor types
of a peptide of interest to do prediction including: pseudo amino acid
composition, k-mer composition, k-mer composition (reduced alphabet),
physico-chemical profile and atomic profile.  According to the obtained results,
AntAngioCOOL reached to a satisfactory performance in anti-angiogenic peptide
prediction on a benchmark non-redundant independent test dataset.")
    (license license:gpl2)))

(define-public r-anscombiser
  (package
    (name "r-anscombiser")
    (version "1.1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "anscombiser" version))
              (sha256
               (base32
                "1hakvxgc50zshi5kplg90r0499mihhwvhhz7bshndjxxci1ashkl"))))
    (properties `((upstream-name . "anscombiser")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://paulnorthrop.github.io/anscombiser/")
    (synopsis "Create Datasets with Identical Summary Statistics")
    (description
     "Anscombe's quartet are a set of four two-variable datasets that have several
common summary statistics but which have very different joint distributions.
This becomes apparent when the data are plotted, which illustrates the
importance of using graphical displays in Statistics.  This package enables the
creation of datasets that have identical marginal sample means and sample
variances, sample correlation, least squares regression coefficients and
coefficient of determination.  The user supplies an initial dataset, which is
shifted, scaled and rotated in order to achieve target summary statistics.  The
general shape of the initial dataset is retained.  The target statistics can be
supplied directly or calculated based on a user-supplied dataset.  The
datasauRus package <https://cran.r-project.org/package=datasauRus> provides
further examples of datasets that have markedly different scatter plots but
share many sample summary statistics.")
    (license license:gpl2+)))

(define-public r-anovir
  (package
    (name "r-anovir")
    (version "0.1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "anovir" version))
              (sha256
               (base32
                "1x7lvj7xchbv6siyc9miivmf0rlxrjflal4icyvbxgdr285s2s9w"))))
    (properties `((upstream-name . "anovir")))
    (build-system r-build-system)
    (propagated-inputs (list r-bbmle))
    (native-inputs (list r-knitr))
    (home-page "https://www.biorxiv.org/content/10.1101/530709v1")
    (synopsis "Analysis of Virulence")
    (description
     "Epidemiological population dynamics models traditionally define a pathogen's
virulence as the increase in the per capita rate of mortality of infected hosts
due to infection.  This package provides functions allowing virulence to be
estimated by maximum likelihood techniques.  The approach is based on the
analysis of relative survival comparing survival in matching cohorts of infected
vs. uninfected hosts (Agnew 2019) <doi:10.1101/530709>.")
    (license license:gpl3)))

(define-public r-anovashiny2
  (package
    (name "r-anovashiny2")
    (version "0.1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ANOVAShiny2" version))
              (sha256
               (base32
                "0bnxfg5c37wi5g53jd0zqq31yx29zvlk2m2jh6jlwki8khpp9y00"))))
    (properties `((upstream-name . "ANOVAShiny2")))
    (build-system r-build-system)
    (propagated-inputs (list r-shiny
                             r-rmarkdown
                             r-rhandsontable
                             r-hh
                             r-dplyr
                             r-desctools))
    (home-page "https://cran.r-project.org/package=ANOVAShiny2")
    (synopsis "Interactive Document for Working with Analysis of Variance")
    (description
     "An interactive document on the topic of one-way and two-way analysis of variance
using rmarkdown and shiny packages.  Runtime examples are provided in the
package function as well as at <https://kartikeyab.shinyapps.io/ANOVAShiny/>.")
    (license license:gpl2)))

(define-public r-anovashiny
  (package
    (name "r-anovashiny")
    (version "0.1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ANOVAShiny" version))
              (sha256
               (base32
                "1z8wi8c8j3rlchfk1vx101qz1r9j2jl5lfh72y5lqsisqxl2fyyz"))))
    (properties `((upstream-name . "ANOVAShiny")))
    (build-system r-build-system)
    (propagated-inputs (list r-shiny
                             r-rmarkdown
                             r-rhandsontable
                             r-hh
                             r-dplyr
                             r-desctools))
    (home-page "https://cran.r-project.org/package=ANOVAShiny")
    (synopsis "Interactive Document for Working with Analysis of Variance")
    (description
     "An interactive document on the topic of one-way and two-way analysis of variance
using rmarkdown and shiny packages.  Runtime examples are provided in the
package function as well as at <https://kartikeyab.shinyapps.io/ANOVAShiny/>.")
    (license license:gpl2)))

(define-public r-anovareplication
  (package
    (name "r-anovareplication")
    (version "1.1.5")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ANOVAreplication" version))
              (sha256
               (base32
                "1d2r2cwpn9rdfbmiccag487pvsq6adn7b321c5z8i7n671h2wi26"))))
    (properties `((upstream-name . "ANOVAreplication")))
    (build-system r-build-system)
    (propagated-inputs (list r-shiny r-quadprog))
    (native-inputs (list r-knitr))
    (home-page "https://dx.doi.org/10.17605/OSF.IO/6H8X3")
    (synopsis
     "Test ANOVA Replications by Means of the Prior Predictive p-Value")
    (description
     "Allows for the computation of a prior predictive p-value to test replication of
relevant features of original ANOVA studies.  Relevant features are captured in
informative hypotheses.  The package also allows for the computation of sample
sizes for new studies, post-hoc power calculations, and comes with a Shiny
application in which all calculations can be conducted as well.  The statistical
underpinnings are described in Zondervan-Zwijnenburg (2019)
<doi:10.31234/osf.io/6myqh>.")
    (license license:gpl3+)))

(define-public r-anovaireva
  (package
    (name "r-anovaireva")
    (version "0.1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ANOVAIREVA" version))
              (sha256
               (base32
                "04z2g79nnh5yhn4aqw0i7ck2b1z5dbasf1zp1sj6rjjrp9aqmaa6"))))
    (properties `((upstream-name . "ANOVAIREVA")))
    (build-system r-build-system)
    (propagated-inputs (list r-shiny
                             r-rmarkdown
                             r-plotly
                             r-ggplot2
                             r-dplyr
                             r-car))
    (home-page "https://cran.r-project.org/package=ANOVAIREVA")
    (synopsis "Interactive Document for Working with Analysis of Variance")
    (description
     "An interactive document on the topic of one-way and two-way analysis of variance
using rmarkdown and shiny packages.  Runtime examples are provided in the
package function as well as at <https://tinyurl.com/ANOVAStatsTool>.")
    (license license:gpl2)))

(define-public r-anomaly
  (package
    (name "r-anomaly")
    (version "4.0.2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "anomaly" version))
              (sha256
               (base32
                "110rdzz6l80vjc0q0gb0f829vb70r97p19ywa7gbl2cbkj2s1cci"))))
    (properties `((upstream-name . "anomaly")))
    (build-system r-build-system)
    (propagated-inputs (list r-zoo
                             r-xts
                             r-runner
                             r-robustbase
                             r-robust
                             r-rlang
                             r-reshape2
                             r-rdpack
                             r-rcpp
                             r-magrittr
                             r-ggplot2
                             r-dplyr
                             r-cowplot
                             r-catools
                             r-bh
                             r-assertive))
    (home-page "https://cran.r-project.org/package=anomaly")
    (synopsis "Detecting Anomalies in Data")
    (description
     "This package implements Collective And Point Anomaly (CAPA) <arXiv:1806.01947>,
Multi-Variate Collective And Point Anomaly (MVCAPA) <arXiv:1909.01691>,
Proportion Adaptive Segment Selection (PASS) <doi:10.1093/biomet/ass059>, and
Bayesian Abnormal Region Detector (BARD) <arXiv:1412.5565> methods for the
detection of anomalies in time series data.  Also includes sequential versions
of CAPA and MVCAPA <arXiv:2009.06670>.")
    (license (list license:gpl2+ license:gpl3+))))

(define-public r-anomalize
  (package
    (name "r-anomalize")
    (version "0.2.2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "anomalize" version))
              (sha256
               (base32
                "13ncx17hdwv7799s7y6p3wvf59dad97y8rs9p56cbd91f6jkjgs5"))))
    (properties `((upstream-name . "anomalize")))
    (build-system r-build-system)
    (propagated-inputs (list r-timetk
                             r-tidyr
                             r-tibbletime
                             r-tibble
                             r-sweep
                             r-rstudioapi
                             r-rlang
                             r-purrr
                             r-glue
                             r-ggplot2
                             r-dplyr
                             r-crayon
                             r-cli))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/business-science/anomalize")
    (synopsis "Tidy Anomaly Detection")
    (description
     "The anomalize package enables a \"tidy\" workflow for detecting anomalies in data.
 The main functions are time_decompose(), anomalize(), and time_recompose().
When combined, it's quite simple to decompose time series, detect anomalies, and
create bands separating the \"normal\" data from the anomalous data at scale (i.e.
 for multiple time series).  Time series decomposition is used to remove trend
and seasonal components via the time_decompose() function and methods include
seasonal decomposition of time series by Loess (\"stl\") and seasonal
decomposition by piecewise medians (\"twitter\").  The anomalize() function
implements two methods for anomaly detection of residuals including using an
inner quartile range (\"iqr\") and generalized extreme studentized deviation
(\"gesd\").  These methods are based on those used in the forecast package and the
Twitter AnomalyDetection package.  Refer to the associated functions for
specific references for these methods.")
    (license license:gpl3+)))

(define-public r-anom
  (package
    (name "r-anom")
    (version "0.5")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ANOM" version))
              (sha256
               (base32
                "14nfy9xplbabfprwxz5fvx26nmqhp657vr6d90dc8vk8ds63ckiz"))))
    (properties `((upstream-name . "ANOM")))
    (build-system r-build-system)
    (propagated-inputs (list r-simcomp r-nparcomp r-multcomp r-mcpan r-ggplot2))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/PhilipPallmann/ANOM")
    (synopsis "Analysis of Means")
    (description
     "Analysis of means (ANOM) as used in technometrical computing.  The package takes
results from multiple comparisons with the grand mean (obtained with multcomp',
SimComp', nparcomp', or MCPAN') or corresponding simultaneous confidence
intervals as input and produces ANOM decision charts that illustrate which group
means deviate significantly from the grand mean.")
    (license license:gpl2+)))

(define-public r-anocva
  (package
    (name "r-anocva")
    (version "0.1.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "anocva" version))
              (sha256
               (base32
                "1byg40jla71k1901js5h9yq89j63d00vkm60id1fxlpv95c4wdrr"))))
    (properties `((upstream-name . "anocva")))
    (build-system r-build-system)
    (propagated-inputs (list r-cluster))
    (home-page "https://cran.r-project.org/package=anocva")
    (synopsis
     "Non-Parametric Statistical Test to Compare Clustering Structures")
    (description
     "This package provides ANOCVA (ANalysis Of Cluster VAriability), a non-parametric
statistical test to compare clustering structures with applications in
functional magnetic resonance imaging data (fMRI).  The ANOCVA allows us to
compare the clustering structure of multiple groups simultaneously and also to
identify features that contribute to the differential clustering.")
    (license license:gpl3+)))

(define-public r-annuityrir
  (package
    (name "r-annuityrir")
    (version "1.0-0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AnnuityRIR" version))
              (sha256
               (base32
                "0yvfqzwhm5nhywfhzkxkfm07c0qi6z21j1cdaypz89qn567aj1d9"))))
    (properties `((upstream-name . "AnnuityRIR")))
    (build-system r-build-system)
    (propagated-inputs (list r-tseries r-mc2d r-fitdistrplus r-envstats
                             r-actuar))
    (home-page "https://www.r-project.org")
    (synopsis "Annuity Random Interest Rates")
    (description
     "Annuity Random Interest Rates proposes different techniques for the
approximation of the present and final value of a unitary annuity-due or
annuity-immediate considering interest rate as a random variable.  Cruz Rambaud
et al. (2017) <doi:10.1007/978-3-319-54819-7_16>.  Cruz Rambaud et al. (2015)
<doi:10.23755/rm.v28i1.25>.")
    (license license:gpl2+)))

(define-public r-annotator
  (package
    (name "r-annotator")
    (version "0.0.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "annotator" version))
              (sha256
               (base32
                "1llr17ac1sr5ih8k5gy8rzmbjhqr3iv0xz3bh3havhlcwlcrpvj0"))))
    (properties `((upstream-name . "annotator")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr
                             r-shiny
                             r-knitr
                             r-imager
                             r-htmlwidgets
                             r-glue))
    (home-page "https://cran.r-project.org/package=annotator")
    (synopsis "Image Annotation and Polygon Outlining using Free Drawing")
    (description
     "This package provides functions to create image annotations through polygon
outlining.  Annotator has the same function as graphics::locator() but achieves
its purpose through drawing, rather than multiple mouse clicks.  It is based on
the htmlwidgets package and fabric.js JavaScript library <http://fabricjs.com/>.")
    (license license:gpl3+)))

(define-public r-annotationbustr
  (package
    (name "r-annotationbustr")
    (version "1.3.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AnnotationBustR" version))
              (sha256
               (base32
                "1q5yxzzmzvw1r64r4y0xh1fiyhaqbx5q4lzpawqaggra4w9igdl8"))))
    (properties `((upstream-name . "AnnotationBustR")))
    (build-system r-build-system)
    (propagated-inputs (list r-seqinr r-ape))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/sborstein/AnnotationBustR")
    (synopsis "Extract Subsequences from GenBank Annotations")
    (description
     "Extraction of subsequences into FASTA files from GenBank annotations where gene
names may vary among accessions.  Borstein & O'Meara (2018)
<doi:10.7717/peerj.5179>.")
    (license license:gpl2+)))

(define-public r-annotater
  (package
    (name "r-annotater")
    (version "0.2.2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "annotater" version))
              (sha256
               (base32
                "1yzsamy4zrr7v0kjnc3x034a7ffw1zj7cc5dx11pcwyhk88yba7z"))))
    (properties `((upstream-name . "annotater")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-tibble
                             r-stringr
                             r-stringi
                             r-rstudioapi
                             r-rlang
                             r-readr
                             r-purrr
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/luisDVA/annotater")
    (synopsis "Annotate Package Load Calls")
    (description
     "This package provides non-invasive annotation of package load calls such as
\\code{library()}, \\code{p_load()}, and \\code{require()} so that we can have an
idea of what the packages we are loading are meant for.")
    (license license:expat)))

(define-public r-annoprobe
  (package
    (name "r-annoprobe")
    (version "0.1.7")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AnnoProbe" version))
              (sha256
               (base32
                "0715bpifj8r4ji0m89wk4x7vd3pwx8kqy9vs8m0ivmq7bb56nx0b"))))
    (properties `((upstream-name . "AnnoProbe")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml2
                             r-pheatmap
                             r-httr
                             r-ggpubr
                             r-ggplot2
                             r-dt
                             r-curl
                             r-biobase))
    (home-page "https://github.com/jmzeng1314/AnnoProbe")
    (synopsis "Annotate the Gene Symbols for Probes in Expression Array")
    (description
     "We curated 147 of expression array, from 3 species(human,mouse,rat), 3
companies('Affymetrix','Illumina','Agilent'), by aligning the Fasta sequences of
all probes of each platform to their corresponding reference genome, and then
annotate them to genes.")
    (license (license:fsdg-compatible "Apache License (>= 2)"))))

(define-public r-ann2
  (package
    (name "r-ann2")
    (version "2.3.4")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ANN2" version))
              (sha256
               (base32
                "1izljhz3rkzq05dkvg9q3fdyj7q871j8lsky67d5r8ffpzm1lk3z"))))
    (properties `((upstream-name . "ANN2")))
    (build-system r-build-system)
    (propagated-inputs (list r-viridislite
                             r-testthat
                             r-reshape2
                             r-rcpparmadillo
                             r-rcpp
                             r-ggplot2))
    (home-page "https://github.com/bflammers/ANN2")
    (synopsis "Artificial Neural Networks for Anomaly Detection")
    (description
     "Training of neural networks for classification and regression tasks using
mini-batch gradient descent.  Special features include a function for training
autoencoders, which can be used to detect anomalies, and some related plotting
functions.  Multiple activation functions are supported, including tanh, relu,
step and ramp.  For the use of the step and ramp activation functions in
detecting anomalies using autoencoders, see Hawkins et al. (2002)
<doi:10.1007/3-540-46145-0_17>.  Furthermore, several loss functions are
supported, including robust ones such as Huber and pseudo-Huber loss, as well as
L1 and L2 regularization.  The possible options for optimization algorithms are
RMSprop, Adam and SGD with momentum.  The package contains a vectorized C++
implementation that facilitates fast training through mini-batch learning.")
    (license (list license:gpl3+
                   (license:fsdg-compatible "file://LICENSE")))))

(define-public r-anmc
  (package
    (name "r-anmc")
    (version "0.2.3")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "anMC" version))
              (sha256
               (base32
                "01j3zbx5ihi1jlbffib7wpv7908lrjgkq8al1mkhh1qrihsj77qb"))))
    (properties `((upstream-name . "anMC")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpparmadillo r-rcpp r-mvtnorm))
    (home-page "https://doi.org/10.1080/10618600.2017.1360781")
    (synopsis "Compute High Dimensional Orthant Probabilities")
    (description
     "Computationally efficient method to estimate orthant probabilities of
high-dimensional Gaussian vectors.  Further implements a function to compute
conservative estimates of excursion sets under Gaussian random field priors.")
    (license license:gpl3)))

(define-public r-aniview
  (package
    (name "r-aniview")
    (version "0.1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "aniview" version))
              (sha256
               (base32
                "1klakkmdk4xllaxd0pllvxi4396n6rz2idz55niy91mp0fhcjhwf"))))
    (properties `((upstream-name . "aniview")))
    (build-system r-build-system)
    (propagated-inputs (list r-jsonlite r-htmltools))
    (home-page "https://felixluginbuhl.com/aniview")
    (synopsis "Animate Shiny and R Markdown Content when it Comes into View")
    (description
     "Animate Shiny and R Markdown content when it comes into view using animate-css
effects thanks to jQuery AniView'.")
    (license license:expat)))

(define-public r-anipaths
  (package
    (name "r-anipaths")
    (version "0.10.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "anipaths" version))
              (sha256
               (base32
                "14shy474795mivxvn0vyfgzwabvhxafgjazcwhz2250smjzdhw03"))))
    (properties `((upstream-name . "anipaths")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyselect
                             r-tidyr
                             r-stringr
                             r-sp
                             r-scales
                             r-rcolorbrewer
                             r-raster
                             r-mgcv
                             r-magrittr
                             r-lubridate
                             r-igraph
                             r-ggplot2
                             r-ggmap
                             r-ellipse
                             r-dplyr
                             r-crawl
                             r-animation))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=anipaths")
    (synopsis "Animation of Multiple Trajectories with Uncertainty")
    (description
     "Animation of observed trajectories using spline-based interpolation (see for
example, Buderman, F. E., Hooten, M. B., Ivan, J. S. and Shenk, T. M. (2016),
<doi:10.1111/2041-210X.12465> \"A functional model for characterizing
long-distance movement behaviour\".  Methods Ecol Evol).  Intended to be used
exploratory data analysis, and perhaps for preparation of presentations.")
    (license license:gpl3)))

(define-public r-animl
  (package
    (name "r-animl")
    (version "1.0.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "animl" version))
              (sha256
               (base32
                "0rc82y5z1jkd9bfq2dnn50sr2lf6vhs7yyn1fwfn13krczc9zcbp"))))
    (properties `((upstream-name . "animl")))
    (build-system r-build-system)
    (propagated-inputs (list r-tfdatasets
                             r-reticulate
                             r-pbapply
                             r-keras
                             r-jpeg
                             r-imager
                             r-exifr
                             r-dplyr
                             r-data-table
                             r-av))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=animl")
    (synopsis "Collection of ML Tools for Conservation Research")
    (description
     "This package provides functions required to classify subjects within camera trap
field data.  The package can handle both images and videos.  The authors
recommend a two-step approach using Microsoft's MegaDector model and then a
second model trained on the classes of interest.")
    (license license:expat)))

(define-public r-animint2
  (package
    (name "r-animint2")
    (version "2022.9.14")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "animint2" version))
              (sha256
               (base32
                "0irnpqhy1lys0w3r0yni7hnf7bbgrcy5062nfm4rngzrfaq1g5z9"))))
    (properties `((upstream-name . "animint2")))
    (build-system r-build-system)
    (propagated-inputs (list r-scales
                             r-rjsonio
                             r-reshape2
                             r-plyr
                             r-mass
                             r-knitr
                             r-gtable
                             r-digest
                             r-data-table))
    (home-page "https://github.com/tdhock/animint2")
    (synopsis "Animated Interactive Grammar of Graphics")
    (description
     "This package provides functions are provided for defining animated, interactive
data visualizations in R code, and rendering on a web page.  The 2018 Journal of
Computational and Graphical Statistics paper,
<doi:10.1080/10618600.2018.1513367> describes the concepts implemented.")
    (license license:gpl3)))

(define-public r-animaltracker
  (package
    (name "r-animaltracker")
    (version "0.2.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "animaltracker" version))
              (sha256
               (base32
                "1zv2nj4wfskz1lxfgw8l4gyrlv418drk8zl4cw55i5na6a39shcv"))))
    (properties `((upstream-name . "animaltracker")))
    (build-system r-build-system)
    (propagated-inputs (list r-zoo
                             r-tidyr
                             r-tibble
                             r-sp
                             r-shinywidgets
                             r-shinythemes
                             r-shinyjs
                             r-shinycssloaders
                             r-shinybs
                             r-shiny
                             r-scales
                             r-rgdal
                             r-raster
                             r-maptools
                             r-lubridate
                             r-leaflet-extras
                             r-leaflet
                             r-httr
                             r-ggplot2
                             r-geosphere
                             r-forcats
                             r-dplyr))
    (home-page "https://cran.r-project.org/package=animaltracker")
    (synopsis "Animal Tracker")
    (description
     "Utilities for spatial-temporal analysis and visualization of animal (e.g.
cattle) tracking data.  The core feature is a shiny web application for
customized processing of GPS logs, including features for data augmentation
(e.g. elevation lookup), data selection, export, plotting, and statistical
summaries.  A data validation application allows for side-by-side comparison via
time series plots and extreme value detection described by J.P. van Brakel
<https://stackoverflow.com/questions/22583391/peak-signal-detection-in-realtime-timeseries-data/>.")
    (license license:gpl3)))

(define-public r-animaltrack
  (package
    (name "r-animaltrack")
    (version "1.0.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "animalTrack" version))
              (sha256
               (base32
                "0jlvfflpaq64s48sblzh1n1vx8g3870iss97whigri29s6hn79ry"))))
    (properties `((upstream-name . "animalTrack")))
    (build-system r-build-system)
    (propagated-inputs (list r-rgl))
    (home-page "https://cran.r-project.org/package=animalTrack")
    (synopsis
     "Animal track reconstruction for high frequency 2-dimensional (2D) or 3-dimensional (3D) movement data")
    (description
     "2D and 3D animal tracking data can be used to reconstruct tracks through
time/space with correction based on known positions.  3D visualization of animal
position and attitude.")
    (license license:gpl2+)))

(define-public r-animalhabitatnetwork
  (package
    (name "r-animalhabitatnetwork")
    (version "0.1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AnimalHabitatNetwork" version))
              (sha256
               (base32
                "1bhqypkiw5v9w26jbdmhndqj5hjfmf7zwivrq2hgs0zcjxwa8gfn"))))
    (properties `((upstream-name . "AnimalHabitatNetwork")))
    (build-system r-build-system)
    (propagated-inputs (list r-igraph r-ggplot2))
    (home-page "https://cran.r-project.org/package=AnimalHabitatNetwork")
    (synopsis
     "Networks Characterising the Physical Configurations of Animal Habitats")
    (description
     "This package provides functions for generating and visualising networks for
characterising the physical attributes and spatial organisations of habitat
components (i.e.  habitat physical configurations).  The network generating
algorithm first determines the X and Y coordinates of N nodes within a rectangle
with a side length of L and an area of A. Then it computes the pair-wise
Euclidean distance Dij between node i and j, and then a complete network with
1/Dij as link weights is constructed.  Then, the algorithm removes links from
the complete network with the probability as shown in the function ahn_prob().
Such link removals can make the network disconnected whereas a connected network
is wanted.  In such cases, the algorithm rewires one network component to its
spatially nearest neighbouring component and repeat doing this until the network
is connected again.  Finally, it outputs an undirected network (weighted or
unweighted, connected or disconnected).  This package came with a manuscript on
modelling the physical configurations of animal habitats using networks (in
preparation).")
    (license license:gpl3)))

(define-public r-animalekf
  (package
    (name "r-animalekf")
    (version "1.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "animalEKF" version))
              (sha256
               (base32
                "0bq2d2iza0c971731b915cd1k2f7gq2x1k7xv4z91sy73v0jngl5"))))
    (properties `((upstream-name . "animalEKF")))
    (build-system r-build-system)
    (propagated-inputs (list r-sp
                             r-shiny
                             r-rgeos
                             r-rgdal
                             r-png
                             r-plyr
                             r-mvtnorm
                             r-mcmcpack
                             r-matrix
                             r-mass
                             r-maptools
                             r-hdinterval
                             r-ggplot2
                             r-ellipse
                             r-deldir
                             r-colorspace
                             r-bezier))
    (home-page "https://cran.r-project.org/package=animalEKF")
    (synopsis "Extended Kalman Filters for Animal Movement")
    (description
     "Synthetic generation of 1-D and 2-D correlated random walks (CRWs) for animal
movement with behavioral switching, and particle filter estimation of movement
parameters from observed trajectories using Extended Kalman Filter (EKF) model.
See Ackerman (2018)
<https://digital.library.temple.edu/digital/collection/p245801coll10/id/499150>.")
    (license license:gpl2+)))

(define-public r-anim-plots
  (package
    (name "r-anim-plots")
    (version "0.2.2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "anim.plots" version))
              (sha256
               (base32
                "0j786k5kkc1d33q52ki6fp3hnddjv7fv3ss6zjm9hqqgkq34vwqh"))))
    (properties `((upstream-name . "anim.plots")))
    (build-system r-build-system)
    (propagated-inputs (list r-animation))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/hughjonesd/anim.plots")
    (synopsis "Simple Animated Plots for R")
    (description
     "Simple animated versions of basic R plots, using the animation package.
Includes animated versions of plot, barplot, persp, contour, filled.contour,
hist, curve, points, lines, text, symbols, segments, and arrows.")
    (license license:gpl2)))

(define-public r-anidom
  (package
    (name "r-anidom")
    (version "0.1.5")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "aniDom" version))
              (sha256
               (base32
                "04gqq6ibmr7zq8p9cbpxj98afq7yz82gp7prwbq2ymbxnkywwpgq"))))
    (properties `((upstream-name . "aniDom")))
    (build-system r-build-system)
    (propagated-inputs (list r-rptr))
    (home-page "https://cran.r-project.org/package=aniDom")
    (synopsis "Inferring Dominance Hierarchies and Estimating Uncertainty")
    (description
     "Provides: (1) Tools to infer dominance hierarchies based on calculating Elo
scores, but with custom functions to improve estimates in animals with
relatively stable dominance ranks. (2) Tools to plot the shape of the dominance
hierarchy and estimate the uncertainty of a given data set.")
    (license license:gpl2)))

(define-public r-angstroms
  (package
    (name "r-angstroms")
    (version "0.0.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "angstroms" version))
              (sha256
               (base32
                "1k8q4pkb5vcjfp2n2dga3q2ydmdxv020k5qzrb6w01ixrgf15d8l"))))
    (properties `((upstream-name . "angstroms")))
    (build-system r-build-system)
    (propagated-inputs (list r-spbabel
                             r-sp
                             r-raster
                             r-proj4
                             r-ncdf4
                             r-nabor))
    (home-page "https://github.com/mdsumner/angstroms")
    (synopsis "Tools for 'ROMS' the Regional Ocean Modeling System")
    (description
     "Helper functions for working with Regional Ocean Modeling System ROMS output.
See <https://www.myroms.org/> for more information about ROMS'.")
    (license license:gpl3)))

(define-public r-anglercreelsurveysimulation
  (package
    (name "r-anglercreelsurveysimulation")
    (version "1.0.2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AnglerCreelSurveySimulation" version))
              (sha256
               (base32
                "1nhd0i30g5wb5jh96gfaa0lgnbnj0m2vy4gz7v2c3142396zalnx"))))
    (properties `((upstream-name . "AnglerCreelSurveySimulation")))
    (build-system r-build-system)
    (propagated-inputs (list r-ggplot2 r-dplyr))
    (native-inputs (list r-knitr))
    (home-page
     "https://cran.r-project.org/package=AnglerCreelSurveySimulation")
    (synopsis "Simulate a Bus Route Creel Survey of Anglers")
    (description
     "Simulate an angler population, sample the simulated population with a
user-specified survey times, and calculate metrics from a bus route-type creel
survey.")
    (license license:gpl3)))

(define-public r-anesrake
  (package
    (name "r-anesrake")
    (version "0.80")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "anesrake" version))
              (sha256
               (base32
                "1p2g51w80jiadlf4asbnsw46asarzlzr5c1yfhdb31ymqxd7p76q"))))
    (properties `((upstream-name . "anesrake")))
    (build-system r-build-system)
    (propagated-inputs (list r-weights r-hmisc))
    (home-page "https://cran.r-project.org/package=anesrake")
    (synopsis "ANES Raking Implementation")
    (description
     "This package provides a comprehensive system for selecting variables and
weighting data to match the specifications of the American National Election
Studies.  The package includes methods for identifying discrepant variables,
raking data, and assessing the effects of the raking algorithm.  It also allows
automated re-raking if target variables fall outside identified bounds and
allows greater user specification than other available raking algorithms.  A
variety of simple weighted statistics that were previously in this package
(version .55 and earlier) have been moved to the package weights.")
    (license license:gpl2+)))

(define-public r-andurinha
  (package
    (name "r-andurinha")
    (version "0.0.2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "andurinha" version))
              (sha256
               (base32
                "1cpz16zv3al6lmsqsb7dl5v6kml2a0hg084rbmwa4wsyk5ygl8bm"))))
    (properties `((upstream-name . "andurinha")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-signal
                             r-rlang
                             r-plyr
                             r-ggplot2
                             r-cowplot))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/noemiallefs/andurinha")
    (synopsis "Make Spectroscopic Data Processing Easier")
    (description
     "The goal of andurinha is provide a fast and friendly way to process
spectroscopic data.  It is intended for processing several spectra of samples
with similar composition (tens to hundreds of spectra).  It compiles
spectroscopy data files, produces standardized and second derivative spectra,
finds peaks and allows to select the most significant ones based on the second
derivative/absorbance sum spectrum.  It also provides functions for graphic
evaluation of the outputs.")
    (license (list license:gpl2
                   (license:fsdg-compatible "file://LICENSE")))))

(define-public r-andromeda
  (package
    (name "r-andromeda")
    (version "0.6.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "Andromeda" version))
              (sha256
               (base32
                "08n6ccx009mfnzmhgwzracwyf8ad40crmvb0wyg304dn2abgybn8"))))
    (properties `((upstream-name . "Andromeda")))
    (build-system r-build-system)
    (propagated-inputs (list r-zip
                             r-tidyselect
                             r-rsqlite
                             r-rlang
                             r-pillar
                             r-hms
                             r-dplyr
                             r-dbplyr
                             r-dbi
                             r-cli))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/OHDSI/Andromeda")
    (synopsis "Asynchronous Disk-Based Representation of Massive Data")
    (description
     "Storing very large data objects on a local drive, while still making it possible
to manipulate the data in an efficient manner.")
    (license license:asl2.0)))

(define-public r-and
  (package
    (name "r-and")
    (version "0.1.3")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "and" version))
              (sha256
               (base32
                "0i4kalmk600f7ri3m8m46xr2p67ik0w82lbm8c3wghawlgiplav0"))))
    (properties `((upstream-name . "and")))
    (build-system r-build-system)
    (propagated-inputs (list r-rlang r-glue))
    (home-page "https://and.rossellhayes.com")
    (synopsis "Construct Natural-Language Lists with Internationalization")
    (description
     "Construct language-aware lists.  Make \"and\"-separated and \"or\"-separated lists
that automatically conform to the user's language settings.")
    (license license:expat)))

(define-public r-anchorregression
  (package
    (name "r-anchorregression")
    (version "0.1.3")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AnchorRegression" version))
              (sha256
               (base32
                "1bmlxk5j3i9mm71cwz785q5sysp8hsyy0080kgd3ksx78p68ara5"))))
    (properties `((upstream-name . "AnchorRegression")))
    (build-system r-build-system)
    (propagated-inputs (list r-selectiveinference r-mgcv r-glmnet))
    (home-page "https://github.com/simzim96/AnchorRegression")
    (synopsis "Perform AnchorRegression")
    (description
     "This package performs AnchorRegression proposed by Rothenhäusler et al.  2020.
The code is adapted from the original paper repository.
(<https://github.com/rothenhaeusler/anchor-regression>) The code was developed
independently from the authors of the paper.")
    (license license:expat)))

(define-public r-ancestrymapper
  (package
    (name "r-ancestrymapper")
    (version "2.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AncestryMapper" version))
              (sha256
               (base32
                "1fr2y1a5rn7rq8aly94f618kywix32jwysi70nfhaqx8hf4zzprb"))))
    (properties `((upstream-name . "AncestryMapper")))
    (build-system r-build-system)
    (propagated-inputs (list r-svd))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=AncestryMapper")
    (synopsis "Assigning Ancestry Based on Population References")
    (description
     "Assigns genetic ancestry to an individual and studies relationships between
local and global populations.")
    (license license:gpl2)))

(define-public r-anapuce
  (package
    (name "r-anapuce")
    (version "2.3")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "anapuce" version))
              (sha256
               (base32
                "05k3ypy4dc8q4jv0by37k66pdwb1wmsd24i6nciris5knfdy9csg"))))
    (properties `((upstream-name . "anapuce")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=anapuce")
    (synopsis "Tools for Microarray Data Analysis")
    (description
     "This package provides functions for normalisation, differentially analysis of
microarray data and local False Discovery Rate.")
    (license license:gpl2)))

(define-public r-analyzer
  (package
    (name "r-analyzer")
    (version "1.0.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "analyzer" version))
              (sha256
               (base32
                "1729dnghdca7dr4l5cxazg68ipkm63mvk2danwm3bva62sza29p6"))))
    (properties `((upstream-name . "analyzer")))
    (build-system r-build-system)
    (propagated-inputs (list r-gridextra r-ggplot2 r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=analyzer")
    (synopsis "Data Analysis and Automated R Notebook Generation")
    (description
     "Easy data analysis and quality checks which are commonly used in data science.
It combines the tabular and graphical visualization for easier usability.  This
package also creates an R Notebook with detailed data exploration with one
function call.  The notebook can be made interactive.")
    (license license:expat)))

(define-public r-analogueextra
  (package
    (name "r-analogueextra")
    (version "0.1-1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "analogueExtra" version))
              (sha256
               (base32
                "1s3qs10hf6hkna0bicid1mc8x8r449bl93xpgyw6lnsjgh2yx62c"))))
    (properties `((upstream-name . "analogueExtra")))
    (build-system r-build-system)
    (propagated-inputs (list r-vegan3d r-rgl r-analogue))
    (home-page "https://github.com/gavinsimpson/analogueExtra")
    (synopsis "Additional Functions for Use with the Analogue Package")
    (description
     "This package provides additional functionality for the analogue package that is
not required by all users of the main package.")
    (license license:gpl2)))

(define-public r-analogue
  (package
    (name "r-analogue")
    (version "0.17-6")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "analogue" version))
              (sha256
               (base32
                "0c5h8nnbflydv35ja1pfhyx7ifwlriwgcnrmxj5il5lvcr70y1vi"))))
    (properties `((upstream-name . "analogue")))
    (build-system r-build-system)
    (propagated-inputs (list r-vegan
                             r-princurve
                             r-mgcv
                             r-mass
                             r-lattice
                             r-brglm))
    (home-page "https://github.com/gavinsimpson/analogue")
    (synopsis "Analogue and Weighted Averaging Methods for Palaeoecology")
    (description
     "Fits Modern Analogue Technique and Weighted Averaging transfer function models
for prediction of environmental data from species data, and related methods used
in palaeoecology.")
    (license license:gpl2)))

(define-public r-analogsea
  (package
    (name "r-analogsea")
    (version "1.0.6")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "analogsea" version))
              (sha256
               (base32
                "1bcykcsciv4s7071iw3a9sxpd3jslv1sg93mxzyhxy4y2pikg7q0"))))
    (properties `((upstream-name . "analogsea")))
    (build-system r-build-system)
    (propagated-inputs (list r-yaml r-magrittr r-jsonlite r-httr))
    (home-page
     "https://github.com/pachadotdev/analogseahttps://pacha.dev/analogsea/")
    (synopsis "Interface to 'Digital Ocean'")
    (description
     "This package provides a set of functions for interacting with the Digital Ocean
API <https://www.digitalocean.com/>, including creating images, destroying them,
rebooting, getting details on regions, and available images.")
    (license (license:fsdg-compatible "Apache License (>= 2)"))))

(define-public r-anacor
  (package
    (name "r-anacor")
    (version "1.1-4")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "anacor" version))
              (sha256
               (base32
                "0wf9kb8389gc9jy32dr8ap78lychgjnd19jix7wzln4yx78ypqnq"))))
    (properties `((upstream-name . "anacor")))
    (build-system r-build-system)
    (propagated-inputs (list r-fda r-colorspace r-car))
    (home-page "https://r-forge.r-project.org/projects/psychor/")
    (synopsis "Simple and Canonical Correspondence Analysis")
    (description
     "This package performs simple and canonical CA (covariates on rows/columns) on a
two-way frequency table (with missings) by means of SVD. Different scaling
methods (standard, centroid, Benzecri, Goodman) as well as various plots
including confidence ellipsoids are provided.")
    (license license:gpl2)))

(define-public r-anaconda
  (package
    (name "r-anaconda")
    (version "0.1.5")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "Anaconda" version))
              (sha256
               (base32
                "02ars06pmg0f0biy022yz2xf0sdmww9ff9zcpl74gah3sickq9ci"))))
    (properties `((upstream-name . "Anaconda")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcolorbrewer
                             r-rafalib
                             r-plyr
                             r-pheatmap
                             r-lookup
                             r-ggrepel
                             r-ggplot2
                             r-deseq2
                             r-data-table
                             r-ape))
    (home-page "https://github.com/PLStenger/Anaconda")
    (synopsis
     "Targeted Differential and Global Enrichment Analysis of Taxonomic Rank by Shared Asvs")
    (description
     "Targeted differential and global enrichment analysis of taxonomic rank by shared
ASVs (Amplicon Sequence Variant), for high-throughput eDNA sequencing of fungi,
bacteria, and metazoan.  Actually works in two steps: I) Targeted differential
analysis from QIIME2 data and II) Global analysis by Taxon Mann-Whitney U test
analysis from targeted analysis (I) (I) Estimate variance-mean dependence in
count/abundance ASVs data from high-throughput sequencing assays and test for
differential represented ASVs based on a model using the negative binomial
distribution. (II) NCBITaxon_MWU uses continuous measure of significance (such
as fold-change or -log(p-value)) to identify NCBITaxon that are significantly
enriches with either up- or down-represented ASVs.  If the measure is binary (0
or 1) the script will perform a typical NCBITaxon enrichment analysis based
Fisher's exact test: it will show NCBITaxon over-represented among the ASVs that
have 1 as their measure.  On the plot, different fonts are used to indicate
significance and color indicates enrichment with either up (red) or down (blue)
regulated ASVs.  No colors are shown for binary measure analysis.  The tree on
the plot is hierarchical clustering of NCBITaxon based on shared ASVs.
Categories with no branch length between them are subsets of each other.  The
fraction next to the category name indicates the fraction of good ASVs in it;
good ASVs are the ones exceeding the arbitrary absValue cutoff (option in
taxon_mwuPlot()).  For Fisher's based test, specify absValue=0.5.  This value
does not affect statistics and is used for plotting only.  The original idea was
for genes differential expression analysis from Wright et al (2015)
<doi:10.1186/s12864-015-1540-2>; adapted here for taxonomic analysis.  The
Anaconda package makes it possible to carry out these analyses by automatically
creating several graphs and tables and storing them in specially created
subfolders.  You will need your QIIME2 pipeline output for each kingdom (eg;
Fungi and/or Bacteria and/or Metazoan): i) taxonomy.tsv, ii)
taxonomy_RepSeq.tsv, iii) ASV.tsv and iv) SampleSheet_comparison.txt (the latter
being created by you).")
    (license license:gpl2+)))

(define-public r-anacoda
  (package
    (name "r-anacoda")
    (version "0.1.4.4")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AnaCoDa" version))
              (sha256
               (base32
                "1b03bxysvw9v4j3bzsmrjf5ci06v6s83ix89qxy73ba5akf2gb7h"))))
    (properties `((upstream-name . "AnaCoDa")))
    (build-system r-build-system)
    (propagated-inputs (list r-vgam r-rcpp r-mvtnorm))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/clandere/AnaCoDa")
    (synopsis
     "Analysis of Codon Data under Stationarity using a Bayesian Framework")
    (description
     "Is a collection of models to analyze genome scale codon data using a Bayesian
framework.  Provides visualization routines and checkpointing for model
fittings.  Currently published models to analyze gene data for selection on
codon usage based on Ribosome Overhead Cost (ROC) are: ROC (Gilchrist et al.
(2015) <doi:10.1093/gbe/evv087>), and ROC with phi (Wallace & Drummond (2013)
<doi:10.1093/molbev/mst051>).  In addition AnaCoDa contains three currently
unpublished models.  The FONSE (First order approximation On NonSense Error)
model analyzes gene data for selection on codon usage against of nonsense error
rates.  The PA (PAusing time) and PANSE (PAusing time + NonSense Error) models
use ribosome footprinting data to analyze estimate ribosome pausing times with
and without nonsense error rate from ribosome footprinting data.")
    (license license:gpl2+)))

(define-public r-amylogram
  (package
    (name "r-amylogram")
    (version "1.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AmyloGram" version))
              (sha256
               (base32
                "1xdi3i3nw4fzj4d040r55f0gid72gy3vbz5nbdrvapl97zk3kp8c"))))
    (properties `((upstream-name . "AmyloGram")))
    (build-system r-build-system)
    (propagated-inputs (list r-shiny r-seqinr r-ranger r-biogram))
    (home-page "https://github.com/michbur/AmyloGram")
    (synopsis "Prediction of Amyloid Proteins")
    (description
     "Predicts amyloid proteins using random forests trained on the n-gram encoded
peptides.  The implemented algorithm can be accessed from both the command line
and shiny-based GUI.")
    (license license:gpl3)))

(define-public r-amt
  (package
    (name "r-amt")
    (version "0.1.7")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "amt" version))
              (sha256
               (base32
                "04sjvb4zvalv22q90n50rdkkj002vr5shhpgxacaac7hy0pgpcyc"))))
    (properties `((upstream-name . "amt")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-tibble
                             r-survival
                             r-sp
                             r-sf
                             r-rlang
                             r-rgeos
                             r-rdpack
                             r-rcpp
                             r-raster
                             r-purrr
                             r-magrittr
                             r-lubridate
                             r-fitdistrplus
                             r-dplyr
                             r-ctmm
                             r-circular
                             r-checkmate))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/jmsigner/amt")
    (synopsis "Animal Movement Tools")
    (description
     "Manage and analyze animal movement data.  The functionality of amt includes
methods to calculate home ranges, track statistics (e.g. step lengths, speed, or
turning angles), prepare data for fitting habitat selection analyses, and
simulation of space-use from fitted step-selection functions.")
    (license license:gpl3)))

(define-public r-amr
  (package
    (name "r-amr")
    (version "1.8.2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AMR" version))
              (sha256
               (base32
                "1d47akk1amf9x28a3ss0j2453hk9rdqkzdklxnv40b13hvjd8l0n"))))
    (properties `((upstream-name . "AMR")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://msberends.github.io/AMR/")
    (synopsis "Antimicrobial Resistance Data Analysis")
    (description
     "This package provides functions to simplify and standardise antimicrobial
resistance (AMR) data analysis and to work with microbial and antimicrobial
properties by using evidence-based methods, as described in
<doi:10.18637/jss.v104.i03>.")
    (license (list license:gpl2
                   (license:fsdg-compatible "file://LICENSE")))))

(define-public r-ampliconduo
  (package
    (name "r-ampliconduo")
    (version "1.1.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AmpliconDuo" version))
              (sha256
               (base32
                "0vw06x47vc0dqzafgpkn4abdsrhxfs9dq8nnrr2pl49skj5n4hks"))))
    (properties `((upstream-name . "AmpliconDuo")))
    (build-system r-build-system)
    (propagated-inputs (list r-xtable r-ggplot2))
    (home-page "https://cran.r-project.org/package=AmpliconDuo")
    (synopsis
     "Statistical Analysis of Amplicon Data of the Same Sample to Identify Artefacts")
    (description
     "Increasingly powerful techniques for high-throughput sequencing open the
possibility to comprehensively characterize microbial communities, including
rare species.  However, a still unresolved issue are the substantial error rates
in the experimental process generating these sequences.  To overcome these
limitations we propose an approach, where each sample is split and the same
amplification and sequencing protocol is applied to both halves.  This procedure
should allow to detect likely PCR and sequencing artifacts, and true rare
species by comparison of the results of both parts.  The AmpliconDuo package,
whereas amplicon duo from here on refers to the two amplicon data sets of a
split sample, is intended to help interpret the obtained read frequency
distribution across split samples, and to filter the false positive reads.")
    (license license:gpl3+)))

(define-public r-ample
  (package
    (name "r-ample")
    (version "1.0.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AMPLE" version))
              (sha256
               (base32
                "1bi39liky0lmv56rxcrf4m9vc3s4xi1z2wcigfkpvsap4gy67qph"))))
    (properties `((upstream-name . "AMPLE")))
    (build-system r-build-system)
    (propagated-inputs (list r-shinyscreenshot
                             r-shinyjs
                             r-shiny
                             r-scales
                             r-rcolorbrewer
                             r-r6
                             r-markdown
                             r-ggplot2))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/PacificCommunity/ofp-sam-ample")
    (synopsis
     "Shiny Apps to Support Capacity Building on Harvest Control Rules")
    (description
     "Three Shiny apps are provided that introduce Harvest Control Rules (HCR) for
fisheries management.  Introduction to HCRs provides a simple overview to how
HCRs work.  Users are able to select their own HCR and step through its
performance, year by year.  Biological variability and estimation uncertainty
are introduced.  Measuring performance builds on the previous app and introduces
the idea of using performance indicators to measure HCR performance.  Comparing
performance allows multiple HCRs to be created and tested, and their performance
compared so that the preferred HCR can be selected.")
    (license license:gpl3+)))

(define-public r-ampir
  (package
    (name "r-ampir")
    (version "1.1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ampir" version))
              (sha256
               (base32
                "0nnsxrnq3m1frrjp3i8bhm67x6xnl0scyb67wxgm5x7b187svhfj"))))
    (properties `((upstream-name . "ampir")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpp r-peptides r-kernlab r-caret))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/Legana/ampir")
    (synopsis "Predict Antimicrobial Peptides")
    (description
     "This package provides a toolkit to predict antimicrobial peptides from protein
sequences on a genome-wide scale.  It incorporates two support vector machine
models (\"precursor\" and \"mature\") trained on publicly available antimicrobial
peptide data using calculated physico-chemical and compositional sequence
properties described in Meher et al. (2017) <doi:10.1038/srep42362>.  In order
to support genome-wide analyses, these models are designed to accept any type of
protein as input and calculation of compositional properties has been optimised
for high-throughput use.  For best results it is important to select the model
that accurately represents your sequence type: for full length proteins, it is
recommended to use the default \"precursor\" model.  The alternative, \"mature\",
model is best suited for mature peptide sequences that represent the final
antimicrobial peptide sequence after post-translational processing.  For details
see Fingerhut et al. (2020) <doi:10.1093/bioinformatics/btaa653>.  The ampir
package is also available via a Shiny based GUI at
<https://ampir.marine-omics.net/>.")
    (license license:gpl2)))

(define-public r-ampgram
  (package
    (name "r-ampgram")
    (version "1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AmpGram" version))
              (sha256
               (base32
                "1j5zx6n8cyzh6dnv96234zmlfj90fs9w4vm32xw8iqgvpcviqyz6"))))
    (properties `((upstream-name . "AmpGram")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringi
                             r-shiny
                             r-ranger
                             r-pbapply
                             r-devtools
                             r-biogram))
    (home-page "https://github.com/michbur/AmpGram")
    (synopsis "Prediction of Antimicrobial Peptides")
    (description
     "Predicts antimicrobial peptides using random forests trained on the n-gram
encoded peptides.  The implemented algorithm can be accessed from both the
command line and shiny-based GUI. The AmpGram model is too large for CRAN and it
has to be downloaded separately from the repository:
<https://github.com/michbur/AmpGramModel>.")
    (license license:gpl3)))

(define-public r-ampd
  (package
    (name "r-ampd")
    (version "0.2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ampd" version))
              (sha256
               (base32
                "0bi8qngd37n60ym516yjcahxc536vdwm60rq5ld32170hww69j7c"))))
    (properties `((upstream-name . "ampd")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=ampd")
    (synopsis
     "An Algorithm for Automatic Peak Detection in Noisy Periodic and Quasi-Periodic Signals")
    (description
     "This package provides a method for automatic detection of peaks in noisy
periodic and quasi-periodic signals.  This method, called automatic
multiscale-based peak detection (AMPD), is based on the calculation and analysis
of the local maxima scalogram, a matrix comprising the scale-dependent
occurrences of local maxima.  For further information see
<doi:10.3390/a5040588>.")
    (license (list license:gpl2+ license:gpl3+))))

(define-public r-amp
  (package
    (name "r-amp")
    (version "1.0.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "amp" version))
              (sha256
               (base32
                "11132s3bdjcldvpws7yc1w4nifvq0iaavdda2zj0wwmi4rw5xx5c"))))
    (properties `((upstream-name . "amp")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-superlearner
                             r-rlang
                             r-mass
                             r-glmnet
                             r-ggplot2
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=amp")
    (synopsis "Statistical Test for the Multivariate Point Null Hypotheses")
    (description
     "This package provides a testing framework for testing the multivariate point
null hypothesis.  A testing framework described in Elder et al. (2022)
<arXiv:2203.01897> to test the multivariate point null hypothesis.  After the
user selects a parameter of interest and defines the assumed data generating
mechanism, this information should be encoded in functions for the parameter
estimator and its corresponding influence curve.  Some parameter and data
generating mechanism combinations have codings in this package, and are
explained in detail in the article.")
    (license license:gpl3+)))

(define-public r-amoudsurv
  (package
    (name "r-amoudsurv")
    (version "0.1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AmoudSurv" version))
              (sha256
               (base32
                "1i5j34wscvqn37lm86dh9fnyn4j6b34rxyb2q6kpn3csyk53x5r9"))))
    (properties `((upstream-name . "AmoudSurv")))
    (build-system r-build-system)
    (propagated-inputs (list r-pracma r-flexsurv r-ahsurv))
    (home-page "https://cran.r-project.org/package=AmoudSurv")
    (synopsis "Tractable Parametric Odds-Based Regression Models")
    (description
     "Fits tractable fully parametric odds-based regression models for survival data,
including proportional odds (PO), accelerated failure time (AFT), accelerated
odds (AO), and General Odds (GO) models in overall survival frameworks.  Given
at least an R function specifying the survivor, hazard rate and cumulative
distribution functions, any user-defined parametric distribution can be fitted.
We applied and evaluated a minimum of seventeen (17) various baseline
distributions that can handle different failure rate shapes for each of the four
different proposed odds-based regression models.  For more information see
Bennet et al., (1983) <doi:10.1002/sim.4780020223>, and Muse et al., (2022)
<doi:10.1016/j.aej.2022.01.033>.")
    (license license:gpl3)))

(define-public r-amnlfa
  (package
    (name "r-amnlfa")
    (version "1.1.2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "aMNLFA" version))
              (sha256
               (base32
                "1bks7g6zc8817gr4j1mxzmyhw23mwafb6816a26vylk8d9k9d315"))))
    (properties `((upstream-name . "aMNLFA")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr
                             r-stringi
                             r-reshape2
                             r-plyr
                             r-mplusautomation
                             r-gridextra
                             r-ggplot2
                             r-dplyr
                             r-devtools))
    (home-page "https://cran.r-project.org/package=aMNLFA")
    (synopsis "Automated Moderated Nonlinear Factor Analysis Using 'M-plus'")
    (description
     "Automated generation, running, and interpretation of moderated nonlinear factor
analysis models for obtaining scores from observed variables, using the method
described by Gottfredson and colleagues (2019)
<doi:10.1016/j.addbeh.2018.10.031>.  This package creates M-plus input files
which may be run iteratively to test two different types of covariate effects on
items: (1) latent variable impact (both mean and variance); and (2) differential
item functioning.  After sequentially testing for all effects, it also creates a
final model by including all significant effects after adjusting for multiple
comparisons.  Finally, the package creates a scoring model which uses the final
values of parameter estimates to generate latent variable scores. \\n\\n This
package generates TEMPLATES for M-plus inputs, which can and should be
inspected, altered, and run by the user.  In addition to being presented without
warranty of any kind, the package is provided under the assumption that everyone
who uses it is reading, interpreting, understanding, and altering every M-plus
input and output file.  There is no one right way to implement moderated
nonlinear factor analysis, and this package exists solely to save users time as
they generate M-plus syntax according to their own judgment.")
    (license license:gpl2)))

(define-public r-ammoniaconcentration
  (package
    (name "r-ammoniaconcentration")
    (version "0.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AmmoniaConcentration" version))
              (sha256
               (base32
                "05pnwfji9l9az4jvni6jy7cayzg5pbspz82a63kmj6rgibn4ywvn"))))
    (properties `((upstream-name . "AmmoniaConcentration")))
    (build-system r-build-system)
    (home-page "https://github.com/tumenas/ammonia")
    (synopsis "Un-Ionized Ammonia Concentration")
    (description
     "This package provides a function to calculate the concentration of un-ionized
ammonia in the total ammonia in aqueous solution using the pH and temperature
values.")
    (license license:expat)))

(define-public r-ammodels
  (package
    (name "r-ammodels")
    (version "0.1.4")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AMModels" version))
              (sha256
               (base32
                "18h075bzk8s75b3zmjd0x8c6dpl40445d4kv8n0p4ldnx80b1aha"))))
    (properties `((upstream-name . "AMModels")))
    (build-system r-build-system)
    (propagated-inputs (list r-unmarked))
    (home-page "https://cran.r-project.org/package=AMModels")
    (synopsis "Adaptive Management Model Manager")
    (description
     "Helps enable adaptive management by codifying knowledge in the form of models
generated from numerous analyses and data sets.  Facilitates this process by
storing all models and data sets in a single object that can be updated and
saved, thus tracking changes in knowledge through time.  A shiny application
called AM Model Manager (modelMgr()) enables the use of these functions via a
GUI.")
    (license license:gpl3)))

(define-public r-ammibayes
  (package
    (name "r-ammibayes")
    (version "1.0-1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ammiBayes" version))
              (sha256
               (base32
                "1m60pg84nhrlhj3kgja766xms2i9dkx0r5vggskfx82mynnlhj9y"))))
    (properties `((upstream-name . "ammiBayes")))
    (build-system r-build-system)
    (propagated-inputs (list r-spam
                             r-msm
                             r-movmf
                             r-latticeextra
                             r-lattice
                             r-hmisc
                             r-distfree-cr
                             r-coda
                             r-bayesplot))
    (home-page "https://cran.r-project.org/package=ammiBayes")
    (synopsis "Bayesian Ammi Model for Continuous Data")
    (description
     "Flexible multi-environment trials analysis via MCMC method for Additive Main
Effects and Multiplicative Model (AMMI) for continuous data.  Biplot with the
averages and regions of confidence can be generated.  The chains run in parallel
on Linux systems and run serially on Windows.")
    (license license:gpl2+)))

(define-public r-amigaffh
  (package
    (name "r-amigaffh")
    (version "0.4.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AmigaFFH" version))
              (sha256
               (base32
                "1iv89nqlqc5lrnz9r56ajgmb54pkk1zafihh1m0528i0hg4l7qxm"))))
    (properties `((upstream-name . "AmigaFFH")))
    (build-system r-build-system)
    (propagated-inputs (list r-vctrs r-tuner))
    (home-page "https://cran.r-project.org/package=AmigaFFH")
    (synopsis "Commodore Amiga File Format Handler")
    (description
     "Modern software often poorly support older file formats.  This package intends
to handle many file formats that were native to the antiquated Commodore Amiga
machine.  This package focuses on file types from the older Amiga operating
systems (<= 3.0).  It will read and write specific file formats and coerces them
into more contemporary data.")
    (license license:gpl3)))

(define-public r-ameshousing
  (package
    (name "r-ameshousing")
    (version "0.0.4")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AmesHousing" version))
              (sha256
               (base32
                "080r0fkmqsdrjgwbmdzacnkmd8py611z54i6r7nzj14r295d5qhk"))))
    (properties `((upstream-name . "AmesHousing")))
    (build-system r-build-system)
    (propagated-inputs (list r-magrittr r-dplyr))
    (home-page "https://github.com/topepo/AmesHousing")
    (synopsis "The Ames Iowa Housing Data")
    (description
     "Raw and processed versions of the data from De Cock (2011)
<http://ww2.amstat.org/publications/jse> are included in the package.")
    (license license:gpl2)))

(define-public r-amerika
  (package
    (name "r-amerika")
    (version "0.1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "amerika" version))
              (sha256
               (base32
                "1c0bi0wrc89d0zv0wzmdvka66mcikgi1w4gn1i22mvg5bivhzaqx"))))
    (properties `((upstream-name . "amerika")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=amerika")
    (synopsis "American Politics-Inspired Color Palette Generator")
    (description
     "This package provides a color palette generator inspired by American politics,
with colors ranging from blue on the left to gray in the middle and red on the
right.  A variety of palettes allow for a range of applications from brief
discrete scales (e.g., three colors for Democrats, Independents, and
Republicans) to continuous interpolated arrays including dozens of shades graded
from blue (left) to red (right).  This package greatly benefitted from building
on the source code (with permission) from Ram and Wickham (2015).")
    (license license:expat)))

(define-public r-amerifluxr
  (package
    (name "r-amerifluxr")
    (version "1.0.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "amerifluxr" version))
              (sha256
               (base32
                "099vv1axgp4jfi9ic4rqsdcv8a5dz1z0zdmdx8r8h474p3jdqm7c"))))
    (properties `((upstream-name . "amerifluxr")))
    (build-system r-build-system)
    (propagated-inputs (list r-readxl
                             r-rcurl
                             r-memoise
                             r-jsonlite
                             r-httr
                             r-heatmaply))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/chuhousen/amerifluxr")
    (synopsis "Interface to 'AmeriFlux' Data Services")
    (description
     "Programmatic interface to the AmeriFlux database (<https://ameriflux.lbl.gov/>).
 Provide query, download, and data summary tools.")
    (license license:bsd-3)))

(define-public r-americancallopt
  (package
    (name "r-americancallopt")
    (version "0.95")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AmericanCallOpt" version))
              (sha256
               (base32
                "1nhy44j5bmmjsp6g79nrn741rzzxikhdnxk4wwbdj9igcc1bs573"))))
    (properties `((upstream-name . "AmericanCallOpt")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=AmericanCallOpt")
    (synopsis
     "This package includes pricing function for selected American call options with underlying assets that generate payouts")
    (description
     "This package includes a set of pricing functions for American call options.  The
following cases are covered: Pricing of an American call using the standard
binomial approximation; Hedge parameters for an American call with a standard
binomial tree; Binomial pricing of an American call with continuous payout from
the underlying asset; Binomial pricing of an American call with an underlying
stock that pays proportional dividends in discrete time; Pricing of an American
call on futures using a binomial approximation; Pricing of a currency futures
American call using a binomial approximation; Pricing of a perpetual American
call.  The user should kindly notice that this material is for educational
purposes only.  The codes are not optimized for computational efficiency as they
are meant to represent standard cases of analytical and numerical solution.")
    (license license:gpl3)))

(define-public r-amen
  (package
    (name "r-amen")
    (version "1.4.4")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "amen" version))
              (sha256
               (base32
                "00c4dw6s8yxagbgadvcpw4ima89aqjqgpm3460zi97xwq9404f1d"))))
    (properties `((upstream-name . "amen")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://github.com/pdhoff/amen")
    (synopsis
     "Additive and Multiplicative Effects Models for Networks and Relational Data")
    (description
     "Analysis of dyadic network and relational data using additive and multiplicative
effects (AME) models.  The basic model includes regression terms, the covariance
structure of the social relations model (Warner, Kenny and Stoto (1979)
<DOI:10.1037/0022-3514.37.10.1742>, Wong (1982) <DOI:10.2307/2287296>), and
multiplicative factor models (Hoff(2009) <DOI:10.1007/s10588-008-9040-4>).
Several different link functions accommodate different relational data
structures, including binary/network data, normal relational data, zero-inflated
positive outcomes using a tobit model, ordinal relational data and data from
fixed-rank nomination schemes.  Several of these link functions are discussed in
Hoff, Fosdick, Volfovsky and Stovel (2013) <DOI:10.1017/nws.2013.17>.
Development of this software was supported in part by NIH grant R01HD067509.")
    (license license:gpl3)))

(define-public r-amelie
  (package
    (name "r-amelie")
    (version "0.2.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "amelie" version))
              (sha256
               (base32
                "0f4rfijskrw9nmyzbrbz6yfa9d0a5cxjw8n9c36hc6jvh377i7k7"))))
    (properties `((upstream-name . "amelie")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=amelie")
    (synopsis "Anomaly Detection with Normal Probability Functions")
    (description
     "This package implements anomaly detection as binary classification for
cross-sectional data.  Uses maximum likelihood estimates and normal probability
functions to classify observations as anomalous.  The method is presented in the
following lecture from the Machine Learning course by Andrew Ng:
<https://www.coursera.org/learn/machine-learning/lecture/C8IJp/algorithm/>, and
is also described in: Aleksandar Lazarevic, Levent Ertoz, Vipin Kumar, Aysel
Ozgur, Jaideep Srivastava (2003) <doi:10.1137/1.9781611972733.3>.")
    (license license:gpl3+)))

(define-public r-amelia
  (package
    (name "r-amelia")
    (version "1.8.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "Amelia" version))
              (sha256
               (base32
                "1r27zjlr8ld932lr6dn79cravss17gry6p0mxgdlbj6g58mfc30j"))))
    (properties `((upstream-name . "Amelia")))
    (build-system r-build-system)
    (propagated-inputs (list r-rlang r-rcpparmadillo r-rcpp r-foreign))
    (native-inputs (list r-knitr))
    (home-page "https://gking.harvard.edu/amelia")
    (synopsis "Program for Missing Data")
    (description
     "This package provides a tool that \"multiply imputes\" missing data in a single
cross-section (such as a survey), from a time series (like variables collected
for each year in a country), or from a time-series-cross-sectional data set
(such as collected by years for each of several countries).  Amelia II
implements our bootstrapping-based algorithm that gives essentially the same
answers as the standard IP or EMis approaches, is usually considerably faster
than existing approaches and can handle many more variables.  Unlike Amelia I
and other statistically rigorous imputation software, it virtually never crashes
(but please let us know if you find to the contrary!).  The program also
generalizes existing approaches by allowing for trends in time series across
observations within a cross-sectional unit, as well as priors that allow experts
to incorporate beliefs they have about the values of missing cells in their
data.  Amelia II also includes useful diagnostics of the fit of multiple
imputation models.  The program works from the R command line or via a graphical
user interface that does not require users to know R.")
    (license license:gpl2+)))

(define-public r-amctestmaker
  (package
    (name "r-amctestmaker")
    (version "1.0.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AMCTestmakeR" version))
              (sha256
               (base32
                "1vgncc61gmqhax2a7072jb36bzkycv80xqihkr5qs8jxnqqkndxd"))))
    (properties `((upstream-name . "AMCTestmakeR")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=AMCTestmakeR")
    (synopsis "Generate LaTeX Code for Auto-Multiple-Choice (AMC)")
    (description
     "Generate code for use with the Optical Mark Recognition free software Auto
Multiple Choice (AMC).  More specifically, this package provides functions that
use as input the question and answer texts, and output the LaTeX code for AMC.")
    (license license:gpl3)))

(define-public r-amcp
  (package
    (name "r-amcp")
    (version "1.0.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AMCP" version))
              (sha256
               (base32
                "14fbb2p4dbgi7i31xxavrldw4wnd4cjjh56ys63rivkswi1hhzj2"))))
    (properties `((upstream-name . "AMCP")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=AMCP")
    (synopsis "Model Comparison Perspective")
    (description
     "Accompanies \"Designing experiments and analyzing data: A model comparison
perspective\" (3rd ed.) by Maxwell, Delaney, & Kelley (2018; Routledge).
Contains all of the data sets in the book's chapters and end-of-chapter
exercises.  Information about the book is available at
<http://www.DesigningExperiments.com>.")
    (license license:gpl3+)))

(define-public r-ambit
  (package
    (name "r-ambit")
    (version "0.1.2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ambit" version))
              (sha256
               (base32
                "1zjsbza5gzr0sfprfxrxrxy3f75r64bi5szk519n2wf5vr4qr7si"))))
    (properties `((upstream-name . "ambit")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpp r-fbasics))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=ambit")
    (synopsis "Simulation and Estimation of Ambit Processes")
    (description
     "Simulation and estimation tools for various types of ambit processes, including
trawl processes and weighted trawl processes.")
    (license license:gpl3)))

(define-public r-ambient
  (package
    (name "r-ambient")
    (version "1.0.2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ambient" version))
              (sha256
               (base32
                "18cmn075yhcbqlrf4gsgqflqzk2d0kc3ah23k9pn47q2dvr6fqn2"))))
    (properties `((upstream-name . "ambient")))
    (build-system r-build-system)
    (propagated-inputs (list r-rlang r-cpp11))
    (home-page "https://ambient.data-imaginist.com")
    (synopsis "Generator of Multidimensional Noise")
    (description
     "Generation of natural looking noise has many application within simulation,
procedural generation, and art, to name a few.  The ambient package provides an
interface to the FastNoise C++ library and allows for efficient generation of
perlin, simplex, worley, cubic, value, and white noise with optional
perturbation in either 2, 3, or 4 (in case of simplex and white noise)
dimensions.")
    (license license:expat)))

(define-public r-ambhasgw
  (package
    (name "r-ambhasgw")
    (version "0.0.2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ambhasGW" version))
              (sha256
               (base32
                "0v517i4whip45pk6bwlwval9pz367pcgzz62b2z22mrwgi6m6bck"))))
    (properties `((upstream-name . "ambhasGW")))
    (build-system r-build-system)
    (propagated-inputs (list r-yaml r-rgdal r-raster))
    (home-page "https://cran.r-project.org/package=ambhasGW")
    (synopsis "Ground Water Modelling")
    (description
     "This package implements distributed transient groundwater modelling.  The model
is based on the groundwater flow equation solved numerically using the finite
difference explicit scheme.")
    (license license:gpl3+)))

(define-public r-amazonadsr
  (package
    (name "r-amazonadsr")
    (version "0.1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "amazonadsR" version))
              (sha256
               (base32
                "1z4c58swpm6y5h4vlxil5ic9larhnn7xkzd9sgggni4878yk0rng"))))
    (properties `((upstream-name . "amazonadsR")))
    (build-system r-build-system)
    (propagated-inputs (list r-jsonlite))
    (native-inputs (list r-knitr))
    (home-page "https://windsor.ai/")
    (synopsis "Get Amazon Ads Data via the 'Windsor.ai' API")
    (description
     "Collect your data on digital marketing campaigns from Amazon Ads using the
Windsor.ai API <https://windsor.ai/api-fields/>.")
    (license license:gpl3)))

(define-public r-amapvox
  (package
    (name "r-amapvox")
    (version "0.12.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AMAPVox" version))
              (sha256
               (base32
                "11achgmgh42q3m50ilxw7laa5v93nq254rl373z7zqk1hvpyy3xk"))))
    (properties `((upstream-name . "AMAPVox")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr
                             r-rvest
                             r-rappdirs
                             r-dplyr
                             r-data-table
                             r-curl))
    (native-inputs (list r-knitr))
    (home-page "https://amapvox.org")
    (synopsis "LiDAR Data Voxelisation")
    (description
     "Read, manipulate and write voxel spaces.  Voxel spaces are read from text-based
output files of the AMAPVox software.  AMAPVox is a LiDAR point cloud
voxelisation software that aims at estimating leaf area through several
theoretical/numerical approaches.  See more in the article Vincent et al. (2017)
<doi:10.23708/1AJNMP> and the technical note Vincent et al. (2021)
<doi:10.23708/1AJNMP>.")
    (license (license:fsdg-compatible "CeCILL (>= 2)"))))

(define-public r-amapro
  (package
    (name "r-amapro")
    (version "0.1.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "amapro" version))
              (sha256
               (base32
                "11g5gfd3f019gdvxljib293a87l6316igj9cq68vxv6xvx4j2cvw"))))
    (properties `((upstream-name . "amapro")))
    (build-system r-build-system)
    (propagated-inputs (list r-shiny r-htmlwidgets))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/helgasoft/amapro/")
    (synopsis "Thin Wrapper for Mapping Library 'AMap' by 'AutoNavi'")
    (description
     "Build and control interactive 2D and 3D maps with R/Shiny'.  Lean set of
powerful commands wrapping native calls to AMap
<https://lbs.amap.com/api/jsapi-v2/summary/>.  Deliver rich mapping
functionality with minimal overhead.")
    (license (license:fsdg-compatible "Apache License (>= 2)"))))

(define-public r-amapgeocode
  (package
    (name "r-amapgeocode")
    (version "0.6.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "amapGeocode" version))
              (sha256
               (base32
                "0j04hg2ks7578fiaymj295yll77xm6x5svmxx6m4n0djky8j10n1"))))
    (properties `((upstream-name . "amapGeocode")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml2
                             r-sjmisc
                             r-magrittr
                             r-jsonlite
                             r-httr
                             r-furrr
                             r-data-table))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/womeimingzi11/amapGeocode")
    (synopsis "An Interface to the 'AutoNavi Maps' API Geocoding Services")
    (description
     "Getting and parsing data of location geocode/reverse-geocode and administrative
regions from AutoNavi Maps'<https://lbs.amap.com/api/webservice/summary> API.")
    (license license:expat)))

(define-public r-amanpg
  (package
    (name "r-amanpg")
    (version "0.3.4")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "amanpg" version))
              (sha256
               (base32
                "19lmf844n2nz8n52lsmabi36bibdd3cc5ry8n1x0aksgspszjb40"))))
    (properties `((upstream-name . "amanpg")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=amanpg")
    (synopsis "Alternating Manifold Proximal Gradient Method for Sparse PCA")
    (description
     "Alternating Manifold Proximal Gradient Method for Sparse PCA uses the
Alternating Manifold Proximal Gradient (AManPG) method to find sparse principal
components from a data or covariance matrix.  Provides a novel algorithm for
solving the sparse principal component analysis problem which provides
advantages over existing methods in terms of efficiency and convergence
guarantees.  Chen, S., Ma, S., Xue, L., & Zou, H. (2020)
<doi:10.1287/ijoo.2019.0032>.  Zou, H., Hastie, T., & Tibshirani, R. (2006)
<doi:10.1198/106186006X113430>.  Zou, H., & Xue, L. (2018)
<doi:10.1109/JPROC.2018.2846588>.")
    (license license:expat)))

(define-public r-amanida
  (package
    (name "r-amanida")
    (version "0.2.3")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "amanida" version))
              (sha256
               (base32
                "0vi1x43s9xbr6ggx6km342qfqn2yppinsgn50gm73vckvb8672gs"))))
    (properties `((upstream-name . "amanida")))
    (build-system r-build-system)
    (propagated-inputs (list r-webchem
                             r-tidyverse
                             r-tidyr
                             r-tibble
                             r-rmarkdown
                             r-readxl
                             r-readr
                             r-magrittr
                             r-knitr
                             r-kableextra
                             r-ggrepel
                             r-ggplot2
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/mariallr/amanida")
    (synopsis "Meta-Analysis for Non-Integral Data")
    (description
     "Combination of results for meta-analysis using significance and effect size
only.  P-values and fold-change are combined to obtain a global significance on
each metabolite.  Produces a volcano plot summarising the relevant results from
meta-analysis.  Vote-counting reports for metabolites.  And explore plot to
detect discrepancies between studies at a first glance.  Methodology is
described in the Llambrich et al. (2021) <doi:10.1093/bioinformatics/btab591>.")
    (license license:gpl3)))

(define-public r-alues
  (package
    (name "r-alues")
    (version "0.2.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ALUES" version))
              (sha256
               (base32
                "12fayxz0cb8wibccgz62gzrbkwzw2y4xljixrh02i1lbfwgsky14"))))
    (properties `((upstream-name . "ALUES")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpp))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/alstat/ALUES/")
    (synopsis "Agricultural Land Use Evaluation System")
    (description
     "Evaluates land suitability for different crops production.  The package is based
on the Food and Agriculture Organization (FAO) and the International Rice
Research Institute (IRRI) methodology for land evaluation.  Development of ALUES
is inspired by similar tool for land evaluation, Land Use Suitability Evaluation
Tool (LUSET).  The package uses fuzzy logic approach to evaluate land
suitability of a particular area based on inputs such as rainfall, temperature,
topography, and soil properties.  The membership functions used for fuzzy
modeling are the following: Triangular, Trapezoidal and Gaussian.  The methods
for computing the overall suitability of a particular area are also included,
and these are the Minimum, Maximum and Average.  Finally, ALUES is a highly
optimized library with core algorithms written in C++.")
    (license license:expat)))

(define-public r-altr2
  (package
    (name "r-altr2")
    (version "1.0.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "altR2" version))
              (sha256
               (base32
                "15nvbq3n76p2857ipyf3q6rs2mwjqsp9gr3rmzbjfm8lrj0faxsv"))))
    (properties `((upstream-name . "altR2")))
    (build-system r-build-system)
    (propagated-inputs (list r-purrr r-gsl))
    (home-page "https://github.com/karchjd/altR2")
    (synopsis "Alternative Estimators to Adjusted R-Squared")
    (description
     "This package provides alternatives to the normal adjusted R-squared estimator
for the estimation of the multiple squared correlation in regression models, as
fitted by the lm() function.  The alternative estimators are described in Karch
(2016) <DOI:10.31234/osf.io/v8dz5>.")
    (license license:gpl2)))

(define-public r-altopt
  (package
    (name "r-altopt")
    (version "0.1.2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ALTopt" version))
              (sha256
               (base32
                "1nbbvniramajg6k83xqgx7r0abjrfja8zz0y3g3j8qmvbcqmjx13"))))
    (properties `((upstream-name . "ALTopt")))
    (build-system r-build-system)
    (propagated-inputs (list r-lattice r-cubature))
    (home-page "https://cran.r-project.org/package=ALTopt")
    (synopsis "Optimal Experimental Designs for Accelerated Life Testing")
    (description
     "This package creates the optimal (D, U and I) designs for the accelerated life
testing with right censoring or interval censoring.  It uses generalized linear
model (GLM) approach to derive the asymptotic variance-covariance matrix of
regression coefficients.  The failure time distribution is assumed to follow
Weibull distribution with a known shape parameter and log-linear link functions
are used to model the relationship between failure time parameters and stress
variables.  The acceleration model may have multiple stress factors, although
most ALTs involve only two or less stress factors.  ALTopt package also provides
several plotting functions including contour plot, Fraction of Use Space (FUS)
plot and Variance Dispersion graphs of Use Space (VDUS) plot.  For more details,
see Seo and Pan (2015) <doi:10.32614/RJ-2015-029>.")
    (license license:gpl3)))

(define-public r-altfuelr
  (package
    (name "r-altfuelr")
    (version "0.1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "altfuelr" version))
              (sha256
               (base32
                "0k3f4wr9gbn5aig40xg817hrnz2lx8g4adyy18s59fs8dw03v87h"))))
    (properties `((upstream-name . "altfuelr")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr
                             r-purrr
                             r-magrittr
                             r-lubridate
                             r-jsonlite
                             r-httr
                             r-dplyr))
    (home-page "https://cran.r-project.org/package=altfuelr")
    (synopsis "Provides an Interface to the NREL Alternate Fuels Locator")
    (description
     "This package provides a number of functions to access the National Energy
Research Laboratory Alternate Fuel Locator API
<https://developer.nrel.gov/docs/transportation/alt-fuel-stations-v1/>.  The
Alternate Fuel Locator shows the location of alternate fuel stations in the
United States and Canada.  This package also includes the data from the US
Department of Energy Alternate Fuel database as a data set.")
    (license license:expat)))

(define-public r-altdoc
  (package
    (name "r-altdoc")
    (version "0.1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "altdoc" version))
              (sha256
               (base32
                "0336p5yc2imr7r7qi1kzl4psy59m8k6c7j4db345n8i61z3dm0ll"))))
    (properties `((upstream-name . "altdoc")))
    (build-system r-build-system)
    (propagated-inputs (list r-yaml
                             r-xslt
                             r-xml2
                             r-usethis
                             r-servr
                             r-rstudioapi
                             r-rmarkdown
                             r-jsonlite
                             r-htmltools
                             r-here
                             r-fs
                             r-desc
                             r-commonmark
                             r-cli))
    (home-page "https://github.com/etiennebacher/altdoc")
    (synopsis
     "Use 'Docsify.js', 'Docute', or 'Mkdocs' to Generate a Package Documentation")
    (description
     "Most developers use pkgdown to create a website for their packages.  Other
documentation generators exist, such as Docute', Docsify.js', or Mkdocs'.  The
aim of altdoc is to provide helpers to create, populate, update, and preview
websites made with these tools.")
    (license license:expat)))

(define-public r-altair
  (package
    (name "r-altair")
    (version "4.2.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "altair" version))
              (sha256
               (base32
                "1132q369yxrfix76xizw22rpbixqbfsf23c3p1m751h536hmx2f6"))))
    (properties `((upstream-name . "altair")))
    (build-system r-build-system)
    (inputs (list python))
    (propagated-inputs (list r-vegawidget
                             r-reticulate
                             r-repr
                             r-magrittr
                             r-htmlwidgets
                             r-assertthat))
    (home-page "https://github.com/vegawidget/altair")
    (synopsis "Interface to 'Altair'")
    (description
     "Interface to Altair <https://altair-viz.github.io>, which itself is a Python
interface to Vega-Lite <https://vega.github.io/vega-lite/>.  This package uses
the Reticulate framework <https://rstudio.github.io/reticulate/> to manage the
interface between R and Python'.")
    (license license:expat)))

(define-public r-altadata
  (package
    (name "r-altadata")
    (version "0.1.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "altadata" version))
              (sha256
               (base32
                "0wv8a0423k0gw5i0qgz5d3wqw22a9pk7r80fp33pn0mxq9b54zdv"))))
    (properties `((upstream-name . "altadata")))
    (build-system r-build-system)
    (propagated-inputs (list r-jsonlite r-httr))
    (home-page "https://github.com/altabering/altadata-r")
    (synopsis "API Wrapper for Altadata.io")
    (description
     "This package provides functions for interacting directly with the ALTADATA API.
With this R package, developers can build applications around the ALTADATA API
without having to deal with accessing and managing requests and responses.
ALTADATA is a curated data marketplace for more information go to
<https://www.altadata.io>.")
    (license license:expat)))

(define-public r-alsm
  (package
    (name "r-alsm")
    (version "0.2.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ALSM" version))
              (sha256
               (base32
                "1g7zk8q462j4faq5wzzghkjc003ny6rj8hrymsgvh3fg3a72lvy3"))))
    (properties `((upstream-name . "ALSM")))
    (build-system r-build-system)
    (propagated-inputs (list r-suppdists r-leaps r-car))
    (home-page "https://cran.r-project.org/package=ALSM")
    (synopsis "Companion to Applied Linear Statistical Models")
    (description
     "This package provides functions and Data set presented in Applied Linear
Statistical Models Fifth Edition (Chapters 1-9 and 16-25), Michael H. Kutner;
Christopher J. Nachtsheim; John Neter; William Li, 2005. (ISBN-10: 0071122214,
ISBN-13: 978-0071122214) that do not exist in R, are gathered in this package.
The whole book will be covered in the next versions.")
    (license (list license:gpl2 license:gpl3))))

(define-public r-alscpc
  (package
    (name "r-alscpc")
    (version "1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ALSCPC" version))
              (sha256
               (base32
                "0ippxzq5qwb9dnpvm1kxhc0fxh83rs9ny5rcvd30w2bp632q9qdx"))))
    (properties `((upstream-name . "ALSCPC")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=ALSCPC")
    (synopsis
     "Accelerated line search algorithm for simultaneous orthogonal transformation of several positive definite symmetric matrices to nearly diagonal form")
    (description
     "Using of the accelerated line search algorithm for simultaneously diagonalize a
set of symmetric positive definite matrices.")
    (license license:gpl2+)))

(define-public r-alr4
  (package
    (name "r-alr4")
    (version "1.0.6")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "alr4" version))
              (sha256
               (base32
                "0v98yzi0fcjxq0ak0w05001h8m9nfa9l0ann9bqvz8bwcmb3jlr2"))))
    (properties `((upstream-name . "alr4")))
    (build-system r-build-system)
    (propagated-inputs (list r-effects r-car))
    (home-page "http://www.z.umn.edu/alr4ed")
    (synopsis "Data to Accompany Applied Linear Regression 4th Edition")
    (description
     "Datasets to Accompany S. Weisberg (2014, ISBN: 978-1-118-38608-8), \"Applied
Linear Regression,\" 4th edition.  Many data files in this package are included
in the `alr3` package as well, so only one of them should be used.")
    (license license:gpl2+)))

(define-public r-alqrfe
  (package
    (name "r-alqrfe")
    (version "1.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "alqrfe" version))
              (sha256
               (base32
                "0lzw1sk4iaqzmg1a39v3wxcgj9hchyjcxq7b3nm83al8r75rfvdk"))))
    (properties `((upstream-name . "alqrfe")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpparmadillo r-rcpp r-mass))
    (home-page "https://cran.r-project.org/package=alqrfe")
    (synopsis "Adaptive Lasso Quantile Regression with Fixed Effects")
    (description
     "Quantile regression with fixed effects solves longitudinal data, considering the
individual intercepts as fixed effects.  The parametric set of this type of
problem used to be huge.  Thus penalized methods such as Lasso are currently
applied.  Adaptive Lasso presents oracle proprieties, which include Gaussianity
and correct model selection.  Bayesian information criteria (BIC) estimates the
optimal tuning parameter lambda.  Plot tools are also available.")
    (license license:gpl2+)))

(define-public r-alphavantager
  (package
    (name "r-alphavantager")
    (version "0.1.2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "alphavantager" version))
              (sha256
               (base32
                "0c97p8njga4xffvsa0kj0s4y0agjr44y9bnjxs5phm1ldcqjs0yj"))))
    (properties `((upstream-name . "alphavantager")))
    (build-system r-build-system)
    (propagated-inputs (list r-timetk
                             r-tidyr
                             r-tibble
                             r-stringr
                             r-readr
                             r-purrr
                             r-jsonlite
                             r-httr
                             r-glue
                             r-dplyr))
    (home-page "https://github.com/business-science/alphavantager")
    (synopsis "Lightweight R Interface to the Alpha Vantage API")
    (description
     "Alpha Vantage has free historical financial information.  All you need to do is
get a free API key at <https://www.alphavantage.co>.  Then you can use the R
interface to retrieve free equity information.  Refer to the Alpha Vantage
website for more information.")
    (license license:gpl3+)))

(define-public r-alphastable
  (package
    (name "r-alphastable")
    (version "0.2.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "alphastable" version))
              (sha256
               (base32
                "01gwrcxlj2jlb8axs5qmrsixk3a8b7044ypyjg6dpdcxfbcf5fvp"))))
    (properties `((upstream-name . "alphastable")))
    (build-system r-build-system)
    (propagated-inputs (list r-stabledist r-nnls r-nlme r-mvtnorm))
    (home-page "https://cran.r-project.org/package=alphastable")
    (synopsis "Inference for Stable Distribution")
    (description
     "Developed to perform the tasks given by the following.  1-computing the
probability density function and distribution function of a univariate stable
distribution; 2- generating from univariate stable, truncated stable,
multivariate elliptically contoured stable, and bivariate strictly stable
distributions; 3- estimating the parameters of univariate symmetric stable, skew
stable, Cauchy, multivariate elliptically contoured stable, and multivariate
strictly stable distributions; 4- estimating the parameters of the mixture of
symmetric stable and mixture of Cauchy distributions.")
    (license license:gpl2+)))

(define-public r-alphasimr
  (package
    (name "r-alphasimr")
    (version "1.3.2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AlphaSimR" version))
              (sha256
               (base32
                "0yps81a9ah9snm1g92adxd4dj19jqmz2j5x4zdsdffhzls0rhw9c"))))
    (properties `((upstream-name . "AlphaSimR")))
    (build-system r-build-system)
    (propagated-inputs (list r-rdpack r-rcpparmadillo r-rcpp r-r6 r-bh))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/gaynorr/AlphaSimR")
    (synopsis "Breeding Program Simulations")
    (description
     "The successor to the AlphaSim software for breeding program simulation [Faux et
al. (2016) <doi:10.3835/plantgenome2016.02.0013>].  Used for stochastic
simulations of breeding programs to the level of DNA sequence for every
individual.  Contained is a wide range of functions for modeling common tasks in
a breeding program, such as selection and crossing.  These functions allow for
constructing simulations of highly complex plant and animal breeding programs
via scripting in the R software environment.  Such simulations can be used to
evaluate overall breeding program performance and conduct research into breeding
program design, such as implementation of genomic selection.  Included is the
Markovian Coalescent Simulator ('MaCS') for fast simulation of biallelic
sequences according to a population demographic history [Chen et al. (2009)
<doi:10.1101/gr.083634.108>].")
    (license license:expat)))

(define-public r-alphashape3d
  (package
    (name "r-alphashape3d")
    (version "1.3.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "alphashape3d" version))
              (sha256
               (base32
                "0d3rxvsb0yl900dlpr1v5w56z8ci9rbp5dlwx7l2laifyprsns2i"))))
    (properties `((upstream-name . "alphashape3d")))
    (build-system r-build-system)
    (propagated-inputs (list r-rgl r-geometry))
    (home-page "https://cran.r-project.org/package=alphashape3d")
    (synopsis
     "Implementation of the 3D Alpha-Shape for the Reconstruction of 3D Sets from a Point Cloud")
    (description
     "Implementation in R of the alpha-shape of a finite set of points in the
three-dimensional space.  The alpha-shape generalizes the convex hull and allows
to recover the shape of non-convex and even non-connected sets in 3D, given a
random sample of points taken into it.  Besides the computation of the
alpha-shape, this package provides users with functions to compute the volume of
the alpha-shape, identify the connected components and facilitate the
three-dimensional graphical visualization of the estimated set.")
    (license license:gpl2)))

(define-public r-alphapart
  (package
    (name "r-alphapart")
    (version "0.9.8")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AlphaPart" version))
              (sha256
               (base32
                "1ih76v3kgnladqq3nvlqrz5sqkg1j97m778kchz6k05cjxhj8l4q"))))
    (properties `((upstream-name . "AlphaPart")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble
                             r-reshape
                             r-rcpp
                             r-pedigree
                             r-magrittr
                             r-ggplot2
                             r-dplyr
                             r-directlabels))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=AlphaPart")
    (synopsis
     "Partition/Decomposition of Breeding Values by Paths of Information")
    (description
     "This package provides a software that implements a method for partitioning
genetic trends to quantify the sources of genetic gain in breeding programmes.
The partitioning method is described in Garcia-Cortes et al. (2008)
<doi:10.1017/S175173110800205X>.  The package includes the main function
AlphaPart for partitioning breeding values and auxiliary functions for
manipulating data and summarizing, visualizing, and saving results.")
    (license license:gpl2+)))

(define-public r-alphaoutlier
  (package
    (name "r-alphaoutlier")
    (version "1.2.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "alphaOutlier" version))
              (sha256
               (base32
                "09yrbv7jsiymw5gzp8p92ki70v1fys2k75x4sb9s7wy3c58wn1cd"))))
    (properties `((upstream-name . "alphaOutlier")))
    (build-system r-build-system)
    (propagated-inputs (list r-rsolnp r-quantreg r-nleqslv))
    (home-page "https://cran.r-project.org/package=alphaOutlier")
    (synopsis
     "Obtain Alpha-Outlier Regions for Well-Known Probability Distributions")
    (description
     "Given the parameters of a distribution, the package uses the concept of
alpha-outliers by Davies and Gather (1993) to flag outliers in a data set.  See
Davies, L.; Gather, U. (1993): The identification of multiple outliers, JASA, 88
423, 782-792, <doi:10.1080/01621459.1993.10476339> for details.")
    (license license:gpl3)))

(define-public r-alphahull3d
  (package
    (name "r-alphahull3d")
    (version "2.0.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AlphaHull3D" version))
              (sha256
               (base32
                "1jp4m2yd9z8m4gz5hfa08qm02kalrzy6pbjf3rfcb0xjglk1lngr"))))
    (properties `((upstream-name . "AlphaHull3D")))
    (build-system r-build-system)
    (inputs (list mpfr gmp))
    (propagated-inputs (list r-rvcg
                             r-rgl
                             r-rcppeigen
                             r-rcppcgal
                             r-rcpp
                             r-bh))
    (native-inputs (list pkg-config))
    (home-page "https://github.com/stla/AlphaHull3D")
    (synopsis "Alpha Hull Computation")
    (description
     "Computation of the alpha hull of a set of points in the 3D space, that is to say
\"something like the shape formed by these points\".  The alpha hull depends on a
positive parameter alpha.  When alpha goes to zero, the alpha hull degenerates
to the set of points, while it is the convex hull of the set of points when
alpha goes to infinity.  Computations are performed by the CGAL C++ library
<https://www.cgal.org/>.")
    (license license:gpl3)))

(define-public r-alphahull
  (package
    (name "r-alphahull")
    (version "2.5")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "alphahull" version))
              (sha256
               (base32
                "04l078vr3cbf1pjm05p9ny566xwsg3zj059gnssn4nwlkc24n442"))))
    (properties `((upstream-name . "alphahull")))
    (build-system r-build-system)
    (propagated-inputs (list r-splancs
                             r-spatstat-random
                             r-spatstat-geom
                             r-sgeostat
                             r-r-utils
                             r-interp
                             r-ggplot2))
    (home-page "https://cran.r-project.org/package=alphahull")
    (synopsis
     "Generalization of the Convex Hull of a Sample of Points in the Plane")
    (description
     "Computation of the alpha-shape and alpha-convex hull of a given sample of points
in the plane.  The concepts of alpha-shape and alpha-convex hull generalize the
definition of the convex hull of a finite set of points.  The programming is
based on the duality between the Voronoi diagram and Delaunay triangulation.
The package also includes a function that returns the Delaunay mesh of a given
sample of points and its dual Voronoi diagram in one single object.")
    (license (list license:gpl2 license:gpl3))))

(define-public r-alphaci
  (package
    (name "r-alphaci")
    (version "1.0.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "alphaci" version))
              (sha256
               (base32
                "1zkj47s1k9qrnbzk6z7rb79yj0sqz7jwzy6m0marzkrakvivqw8k"))))
    (properties `((upstream-name . "alphaci")))
    (build-system r-build-system)
    (propagated-inputs (list r-matrixcalc r-future-apply))
    (native-inputs (list r-knitr))
    (home-page "https://jonasmoss.github.io/alphaci/")
    (synopsis
     "Confidence Intervals for Coefficient Alpha and Standardized Alpha")
    (description
     "Calculate confidence intervals for alpha and standardized alpha using asymptotic
theory or the studentized bootstrap, with or without transformations.  Supports
the asymptotic distribution-free method of Maydeu-Olivares, et al. (2007)
<doi:10.1037/1082-989X.12.2.157>, the pseudo-elliptical method of Yuan & Bentler
(2002) <doi:10.1007/BF02294845>, and the normal method of van Zyl et al. (1999)
<doi:10.1007/BF02296146>, for both coefficient alpha and standardized alpha.")
    (license license:expat)))

(define-public r-alphabetr
  (package
    (name "r-alphabetr")
    (version "0.2.2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "alphabetr" version))
              (sha256
               (base32
                "1pmp6zwhgycb38y5jbvrbv2nza7gyjh508vy09ml483c2cysvc1r"))))
    (properties `((upstream-name . "alphabetr")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpp r-multicool r-dplyr r-clue))
    (native-inputs (list r-knitr))
    (home-page "http://github.com/edwardslee/alphabetr")
    (synopsis
     "Algorithms for High-Throughput Sequencing of Antigen-Specific T Cells")
    (description
     "This package provides algorithms for frequency-based pairing of alpha-beta T
cell receptors.")
    (license license:agpl3+)))

(define-public r-alpaca
  (package
    (name "r-alpaca")
    (version "0.3.4")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "alpaca" version))
              (sha256
               (base32
                "1fqw8fcahpgdkj25pd6pq4isd0yrdpiypl3q9ir79a56pvjcn8a4"))))
    (properties `((upstream-name . "alpaca")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpparmadillo r-rcpp r-mass r-formula
                             r-data-table))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/amrei-stammann/alpaca")
    (synopsis "Fit GLM's with High-Dimensional k-Way Fixed Effects")
    (description
     "This package provides a routine to partial out factors with many levels during
the optimization of the log-likelihood function of the corresponding generalized
linear model (glm).  The package is based on the algorithm described in Stammann
(2018) <arXiv:1707.01815> and is restricted to glm's that are based on maximum
likelihood estimation and nonlinear.  It also offers an efficient algorithm to
recover estimates of the fixed effects in a post-estimation routine and includes
robust and multi-way clustered standard errors.  Further the package provides
analytical bias corrections for binary choice models derived by Fernandez-Val
and Weidner (2016) <doi:10.1016/j.jeconom.2015.12.014> and Hinz, Stammann, and
Wanner (2020) <arXiv:2004.12655>.")
    (license license:gpl3)))

(define-public r-alookr
  (package
    (name "r-alookr")
    (version "0.3.7")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "alookr" version))
              (sha256
               (base32
                "0sdwphzxjh8y4gi3pnsdddra0x085h30m520j8im25z1bhxp0sq7"))))
    (properties `((upstream-name . "alookr")))
    (build-system r-build-system)
    (propagated-inputs (list r-xgboost
                             r-tidyselect
                             r-tidyr
                             r-tibble
                             r-rpart
                             r-rocr
                             r-rlang
                             r-ranger
                             r-randomforest
                             r-purrr
                             r-party
                             r-parallelly
                             r-mlmetrics
                             r-mass
                             r-glmnet
                             r-ggplot2
                             r-ggmosaic
                             r-future
                             r-dplyr
                             r-dlookr
                             r-cli
                             r-catools))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=alookr")
    (synopsis "Model Classifier for Binary Classification")
    (description
     "This package provides a collection of tools that support data splitting,
predictive modeling, and model evaluation.  A typical function is to split a
dataset into a training dataset and a test dataset.  Then compare the data
distribution of the two datasets.  Another feature is to support the development
of predictive models and to compare the performance of several predictive
models, helping to select the best model.")
    (license (list license:gpl2
                   (license:fsdg-compatible "file://LICENSE")))))

(define-public r-almanac
  (package
    (name "r-almanac")
    (version "0.1.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "almanac" version))
              (sha256
               (base32
                "0qsczk74ihy7ac5c4dzd6ax5gfmr56wfnjxg396qc2c3xykb7dd5"))))
    (properties `((upstream-name . "almanac")))
    (build-system r-build-system)
    (propagated-inputs (list r-vctrs
                             r-v8
                             r-rlang
                             r-r6
                             r-magrittr
                             r-lubridate
                             r-glue))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/DavisVaughan/almanac")
    (synopsis "Tools for Working with Recurrence Rules")
    (description
     "This package provides tools for defining recurrence rules and recurrence
bundles.  Recurrence rules are a programmatic way to define a recurring event,
like the first Monday of December.  Multiple recurrence rules can be combined
into larger recurrence bundles.  Together, these provide a system for adjusting
and generating sequences of dates while simultaneously skipping over dates in a
recurrence bundle's event set.")
    (license license:expat)))

(define-public r-allspice
  (package
    (name "r-allspice")
    (version "1.0.5")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "Allspice" version))
              (sha256
               (base32
                "0a99iqb01snza0ad07lrzmn88vpq8wvx5vjr8fk0wbzihxzbzn4y"))))
    (properties `((upstream-name . "Allspice")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=Allspice")
    (synopsis "RNA-Seq Profile Classifier")
    (description
     "We developed a lightweight machine learning tool for RNA profiling of acute
lymphoblastic leukemia (ALL), however, it can be used for any problem where
multiple classes need to be identified from multi-dimensional data.  The
methodology is described in Makinen V-P, Rehn J, Breen J, Yeung D, White DL
(2022) Multi-cohort transcriptomic subtyping of B-cell acute lymphoblastic
leukemia, International Journal of Molecular Sciences 23:4574,
<doi:10.3390/ijms23094574>.  The classifier contains optimized mean profiles of
the classes (centroids) as observed in the training data, and new samples are
matched to these centroids using the shortest Euclidean distance.  Centroids
derived from a dataset of 1,598 ALL patients are included, but users can train
the models with their own data as well.  The output includes both numerical and
visual presentations of the classification results.  Samples with mixed features
from multiple classes or atypical values are also identified.")
    (license license:gpl2+)))

(define-public r-allomr
  (package
    (name "r-allomr")
    (version "0.1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "allomr" version))
              (sha256
               (base32
                "0iprldmqww928m3mic3lcb8vhsr4ihrn83lvlx3wr3n7zch72771"))))
    (properties `((upstream-name . "allomr")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=allomr")
    (synopsis
     "Removing Allometric Effects of Body Size in Morphological Analysis")
    (description
     "Implementation of the technique of Lleonart et al. (2000)
<doi:10.1006/jtbi.2000.2043> to scale body measurements that exhibit an
allometric growth.  This procedure is a theoretical generalization of the
technique used by Thorpe (1975) <doi:10.1111/j.1095-8312.1975.tb00732.x> and
Thorpe (1976) <doi:10.1111/j.1469-185X.1976.tb01063.x>.")
    (license license:gpl3+)))

(define-public r-allestimates
  (package
    (name "r-allestimates")
    (version "0.2.2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "allestimates" version))
              (sha256
               (base32
                "0g0j6q810665lfa3a9xwmv0hkgcp2a8g0xq0vfpvyykyqykgid3z"))))
    (properties `((upstream-name . "allestimates")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-tibble
                             r-survival
                             r-stringr
                             r-speedglm
                             r-ggplot2
                             r-dplyr
                             r-broom))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=allestimates")
    (synopsis "Effect Estimates from All Models")
    (description
     "Estimates and plots effect estimates from models with all possible combinations
of a list of variables.  It can be used for assessing treatment effects in
clinical trials or risk factors in bio-medical and epidemiological research.
Like Stata command confall (Wang Z. Stata Journal 2007; 7, Number 2, pp.
183–196), allestimates calculates and stores all effect estimates, and plots
them against p values or Akaike information criterion (AIC) values.  It
currently has functions for linear regression: all_lm(), logistic and Poisson
regression: all_glm() and all_speedglm(), and Cox proportional hazards
regression: all_cox().")
    (license license:gpl2)))

(define-public r-alleleshift
  (package
    (name "r-alleleshift")
    (version "1.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AlleleShift" version))
              (sha256
               (base32
                "1cmmxwp3qq28hln6k9hfv61b53nwx08iidhcxj8bdwv7msyp9f8k"))))
    (properties `((upstream-name . "AlleleShift")))
    (build-system r-build-system)
    (propagated-inputs (list r-vegan r-biodiversityr r-adegenet))
    (home-page "https://cran.r-project.org/package=AlleleShift")
    (synopsis
     "Predict and Visualize Population-Level Changes in Allele Frequencies in Response to Climate Change")
    (description
     "This package provides methods (<doi:10.7717/peerj.11534>) are provided of
calibrating and predicting shifts in allele frequencies through redundancy
analysis ('vegan::rda()') and generalized additive models ('mgcv::gam()').
Visualization functions for predicted changes in allele frequencies include
shift.dot.ggplot()', shift.pie.ggplot()', shift.moon.ggplot()',
shift.waffle.ggplot() and shift.surf.ggplot() that are made with input data sets
that are prepared by helper functions for each visualization method.  Examples
in the documentation show how to prepare animated climate change graphics
through a time series with the gganimate package.  Function amova.rda() shows
how Analysis of Molecular Variance can be directly conducted with the results
from redundancy analysis.")
    (license license:gpl3)))

(define-public r-alleleretain
  (package
    (name "r-alleleretain")
    (version "2.0.2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AlleleRetain" version))
              (sha256
               (base32
                "0b6h5giskqbjbrk8nf29i75wrhxsjw1c87laiqzrpbp9n717bl20"))))
    (properties `((upstream-name . "AlleleRetain")))
    (build-system r-build-system)
    (home-page "https://sites.google.com/site/alleleretain/")
    (synopsis "Allele Retention, Inbreeding, and Demography")
    (description
     "Simulate the effect of management or demography on allele retention and
inbreeding accumulation in bottlenecked populations of animals with overlapping
generations.")
    (license license:gpl2+)))

(define-public r-allelematch
  (package
    (name "r-allelematch")
    (version "2.5.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "allelematch" version))
              (sha256
               (base32
                "00117cj01psax4rjvy2nja5r2ss9l8zzjicczh46kp401i1ghmwc"))))
    (properties `((upstream-name . "allelematch")))
    (build-system r-build-system)
    (propagated-inputs (list r-dynamictreecut))
    (home-page "https://cran.r-project.org/package=allelematch")
    (synopsis
     "Identifying Unique Multilocus Genotypes where Genotyping Error and Missing Data may be Present")
    (description
     "Tools for the identification of unique of multilocus genotypes when both
genotyping error and missing data may be present.  The package is targeted at
those working with large datasets and databases containing multiple samples of
each individual, a situation that is common in conservation genetics, and
particularly in non-invasive wildlife sampling applications.  Functions
explicitly incorporate missing data, and can tolerate allele mismatches created
by genotyping error.  If you use this tool, please cite the package using the
journal article in Molecular Ecology Resources (Galpern et al., 2012).  Please
use citation('allelematch') to call the full citation.  For users with access to
the associated journal article, tutorial material is also available as
supplementary material to the article describing this software, the citation for
which can be called using citation('allelematch').")
    (license license:gpl3)))

(define-public r-allehap
  (package
    (name "r-allehap")
    (version "0.9.9")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "alleHap" version))
              (sha256
               (base32
                "1fqrw645s3f5363p7jl3dzy8xphxdr1v6wdsjmqcqwpgvjqfr2zz"))))
    (properties `((upstream-name . "alleHap")))
    (build-system r-build-system)
    (propagated-inputs (list r-abind))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=alleHap")
    (synopsis
     "Allele Imputation and Haplotype Reconstruction from Pedigree Databases")
    (description
     "Tools to simulate alphanumeric alleles, impute genetic missing data and
reconstruct non-recombinant haplotypes from pedigree databases in a
deterministic way.  Allelic simulations can be implemented taking into account
many factors (such as number of families, markers, alleles per marker,
probability and proportion of missing genotypes, recombination rate, etc).
Genotype imputation can be used with simulated datasets or real databases
(previously loaded in .ped format).  Haplotype reconstruction can be carried out
even with missing data, since the program firstly imputes each family genotype
(without a reference panel), to later reconstruct the corresponding haplotypes
for each family member.  All this considering that each individual (due to
meiosis) should unequivocally have two alleles per marker (one inherited from
each parent) and thus imputation and reconstruction results can be
deterministically calculated.")
    (license license:gpl2+)))

(define-public r-allcontributors
  (package
    (name "r-allcontributors")
    (version "0.1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "allcontributors" version))
              (sha256
               (base32
                "1lvm6r4k4z4v2pl1nb6v2ql1cakyi48b3vp4zdf0p5rvmv7sndz6"))))
    (properties `((upstream-name . "allcontributors")))
    (build-system r-build-system)
    (propagated-inputs (list r-magrittr
                             r-jsonlite
                             r-httr
                             r-gitcreds
                             r-git2r
                             r-ghql
                             r-curl
                             r-clipr
                             r-cli))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/ropenscilabs/allcontributors")
    (synopsis "Acknowledge all Contributors to a Project")
    (description
     "Acknowledge all contributors to a project via a single function call.  The
function appends to a README or other specified file(s) a table with names of
all individuals who contributed via code or repository issues.  The package also
includes several additional functions to extract and quantify contributions to
any repository.")
    (license license:gpl3)))

(define-public r-alkahest
  (package
    (name "r-alkahest")
    (version "1.0.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "alkahest" version))
              (sha256
               (base32
                "1m9lp12vvlzpsscig1c5y07m7wkj0v8jj9f3bzhb9sp1ii4nyysh"))))
    (properties `((upstream-name . "alkahest")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://packages.tesselle.org/alkahest/")
    (synopsis "Pre-Processing XY Data from Experimental Methods")
    (description
     "This package provides a lightweight, dependency-free toolbox for pre-processing
XY data from experimental methods (i.e.  any signal that can be measured along a
continuous variable).  This package provides methods for baseline estimation and
correction, smoothing, normalization, integration and peaks detection.  Baseline
correction methods includes polynomial fitting as described in Lieber and
Mahadevan-Jansen (2003) <doi:10.1366/000370203322554518>, Rolling Ball algorithm
after Kneen and Annegarn (1996) <doi:10.1016/0168-583X(95)00908-6>, SNIP
algorithm after Ryan et al. (1988) <doi:10.1016/0168-583X(88)90063-8>, 4S Peak
Filling after Liland (2015) <doi:10.1016/j.mex.2015.02.009> and more.")
    (license license:gpl3+)))

(define-public r-aliases2entrez
  (package
    (name "r-aliases2entrez")
    (version "0.1.2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "aliases2entrez" version))
              (sha256
               (base32
                "11myzwvmagnj35qrrxr35hklzv76c0c4h2zl64y3lzzn5rfii0n6"))))
    (properties `((upstream-name . "aliases2entrez")))
    (build-system r-build-system)
    (propagated-inputs (list r-readr
                             r-rcurl
                             r-org-hs-eg-db
                             r-limma
                             r-foreach
                             r-doparallel
                             r-annotationdbi))
    (home-page "https://cran.r-project.org/package=aliases2entrez")
    (synopsis "Converts Human gene symbols to entrez IDs")
    (description
     "Queries multiple resources authors HGNC (2019) <https://www.genenames.org>,
authors limma (2015) <doi:10.1093/nar/gkv007> to find the correspondence between
evolving nomenclature of human gene symbols, aliases, previous symbols or
synonyms with stable, curated gene entrezID from NCBI database.  This allows
fast, accurate and up-to-date correspondence between human gene expression
datasets from various date and platform (e.g: gene symbol: BRCA1 - ID: 672).")
    (license license:expat)))

(define-public r-algorithmia
  (package
    (name "r-algorithmia")
    (version "0.3.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "algorithmia" version))
              (sha256
               (base32
                "1ccmcsyxncyv8k0fjvr5y44amygqi7qx2dy6rsy3a5pw281hllr4"))))
    (properties `((upstream-name . "algorithmia")))
    (build-system r-build-system)
    (propagated-inputs (list r-rjson r-httr r-base64enc))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=algorithmia")
    (synopsis "Allows you to Easily Interact with the Algorithmia Platform")
    (description
     "The company, Algorithmia, houses the largest marketplace of online algorithms.
This package essentially holds a bunch of REST wrappers that make it very easy
to call algorithms in the Algorithmia platform and access files and directories
in the Algorithmia data API. To learn more about the services they offer and the
algorithms in the platform visit <http://algorithmia.com>.  More information for
developers can be found at <https://algorithmia.com/developers>.")
    (license license:expat)))

(define-public r-algo
  (package
    (name "r-algo")
    (version "0.1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "algo" version))
              (sha256
               (base32
                "1g18p8jyj9crkqm16y2im3r9xzqwa36javv4vi1wvsqkg31d81si"))))
    (properties `((upstream-name . "algo")))
    (build-system r-build-system)
    (propagated-inputs (list r-jsonlite r-htmltools r-glue))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/feddelegrand7/algo")
    (synopsis
     "Implement an Address Search Auto Completion Menu on 'Shiny' Text Inputs Using the 'Algolia Places' 'Javascript' Library")
    (description
     "Allows the user to implement an address search auto completion menu on shiny
text inputs.  This is done using the Algolia Places JavaScript library.  See
<https://community.algolia.com/places/>.")
    (license license:expat)))

(define-public r-algebraichaplopackage
  (package
    (name "r-algebraichaplopackage")
    (version "1.2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AlgebraicHaploPackage" version))
              (sha256
               (base32
                "1krm5cx609sv2p0g3xm5jaiqs9li06v717lw7ywjvx7myc9x4c07"))))
    (properties `((upstream-name . "AlgebraicHaploPackage")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=AlgebraicHaploPackage")
    (synopsis "Haplotype Two Snips Out of a Paired Group of Patients")
    (description
     "Two unordered pairs of data of two different snips positions is haplotyped by
resolving a small number ob closed equations.")
    (license license:gpl2)))

(define-public r-algaeclassify
  (package
    (name "r-algaeclassify")
    (version "1.3.2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "algaeClassify" version))
              (sha256
               (base32
                "1ggxyj79ddc3c0q3fn1dbx5rmvq5jqrza9dzswwb9sfpfb8acdfh"))))
    (properties `((upstream-name . "algaeClassify")))
    (build-system r-build-system)
    (propagated-inputs (list r-lubridate))
    (home-page "https://cran.r-project.org/package=algaeClassify")
    (synopsis
     "Determine Phytoplankton Functional Groups Based on Functional Traits")
    (description
     "This package provides functions that facilitate the use of accepted taxonomic
nomenclature, collection of functional trait data, and assignment of functional
group classifications to phytoplankton species.  Possible classifications
include Morpho-functional group (MFG; Salmaso et al.  2015
<doi:10.1111/fwb.12520>) and CSR (Reynolds 1988; Functional morphology and the
adaptive strategies of phytoplankton.  In C.D. Sandgren (ed).  Growth and
reproductive strategies of freshwater phytoplankton, 388-433.  Cambridge
University Press, New York).  Versions 1.3.0 and later no longer include the
algae_search() function for querying the algaebase online taxonomic database
(www.algaebase.org).  Users are advised to verify taxonomic names directly using
algaebase and cite the database in resulting publications.  Note that none of
the algaeClassify authors are affiliated with algaebase in any way.  The
algaeClassify package is a product of the GEISHA (Global Evaluation of the
Impacts of Storms on freshwater Habitat and Structure of phytoplankton
Assemblages), funded by CESAB (Centre for Synthesis and Analysis of
Biodiversity) and the USGS John Wesley Powell Center for Synthesis and Analysis,
with data and other support provided by members of GLEON (Global Lake Ecology
Observation Network).  This software is preliminary or provisional and is
subject to revision.  It is being provided to meet the need for timely best
science.  The software has not received final approval by the U.S. Geological
Survey (USGS).  No warranty, expressed or implied, is made by the USGS or the
U.S. Government as to the functionality of the software and related material nor
shall the fact of release constitute any such warranty.  The software is
provided on the condition that neither the USGS nor the U.S. Government shall be
held liable for any damages resulting from the authorized or unauthorized use of
the software.")
    (license (list license:gpl2 license:gpl3))))

(define-public r-alfred
  (package
    (name "r-alfred")
    (version "0.2.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "alfred" version))
              (sha256
               (base32
                "1y0s6vn0piq4wnlc6v143va0qkklm67aa653lwgq926nfnjxz6as"))))
    (properties `((upstream-name . "alfred")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-tibble
                             r-rlang
                             r-magrittr
                             r-lubridate
                             r-jsonlite
                             r-httr
                             r-dplyr
                             r-curl))
    (home-page "https://github.com/onnokleen/alfred/")
    (synopsis
     "Downloading Time Series from ALFRED Database for Various Vintages")
    (description
     "This package provides direct access to the ALFRED
(<https://alfred.stlouisfed.org>) and FRED (<https://fred.stlouisfed.org>)
databases.  Its functions return tidy data frames for different releases of the
specified time series.  Note that this product uses the FRED© API but is not
endorsed or certified by the Federal Reserve Bank of St.  Louis.")
    (license license:expat)))

(define-public r-alfr
  (package
    (name "r-alfr")
    (version "1.2.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "alfr" version))
              (sha256
               (base32
                "1ldq8gvgqjjabn86hdqb6hxch8x4hvr6djv5ly4mx039dipc8jxi"))))
    (properties `((upstream-name . "alfr")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr r-magrittr r-jsonlite r-httr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/rwetherall/alfr")
    (synopsis "Connectivity to 'Alfresco' Content Management Repositories")
    (description
     "Allows you to connect to an Alfresco content management repository and interact
with its contents using simple and intuitive functions.  You will be able to
establish a connection session to the Alfresco repository, read and upload
content and manage folder hierarchies.  For more details on the Alfresco content
management repository see
<https://www.alfresco.com/ecm-software/document-management>.")
    (license (list license:gpl3
                   (license:fsdg-compatible "file://LICENSE")))))

(define-public r-alfq
  (package
    (name "r-alfq")
    (version "1.3.6")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "aLFQ" version))
              (sha256
               (base32
                "0kphpvhz36859f5l0k8mbf59g9871mynbs4ybdi0h5nm2cdjy9vx"))))
    (properties `((upstream-name . "aLFQ")))
    (build-system r-build-system)
    (propagated-inputs (list r-seqinr
                             r-rocr
                             r-reshape2
                             r-randomforest
                             r-plyr
                             r-lattice
                             r-data-table
                             r-caret
                             r-bio3d))
    (home-page "https://github.com/aLFQ")
    (synopsis
     "Estimating Absolute Protein Quantities from Label-Free LC-MS/MS Proteomics Data")
    (description
     "Determination of absolute protein quantities is necessary for multiple
applications, such as mechanistic modeling of biological systems.  Quantitative
liquid chromatography tandem mass spectrometry (LC-MS/MS) proteomics can measure
relative protein abundance on a system-wide scale.  To estimate absolute
quantitative information using these relative abundance measurements requires
additional information such as heavy-labeled references of known concentration.
Multiple methods have been using different references and strategies; some are
easily available whereas others require more effort on the users end.  Hence, we
believe the field might benefit from making some of these methods available
under an automated framework, which also facilitates validation of the chosen
strategy.  We have implemented the most commonly used absolute label-free
protein abundance estimation methods for LC-MS/MS modes quantifying on either
MS1-, MS2-levels or spectral counts together with validation algorithms to
enable automated data analysis and error estimation.  Specifically, we used
Monte-carlo cross-validation and bootstrapping for model selection and
imputation of proteome-wide absolute protein quantity estimation.  Our
open-source software is written in the statistical programming language R and
validated and demonstrated on a synthetic sample.")
    (license license:gpl3+)))

(define-public r-aleplot
  (package
    (name "r-aleplot")
    (version "1.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ALEPlot" version))
              (sha256
               (base32
                "0bakl8a7xda7vh9zsc66kkd5w5jmb5j28kfwpfq2ifvk2mrakr3w"))))
    (properties `((upstream-name . "ALEPlot")))
    (build-system r-build-system)
    (propagated-inputs (list r-yaimpute))
    (home-page "https://cran.r-project.org/package=ALEPlot")
    (synopsis
     "Accumulated Local Effects (ALE) Plots and Partial Dependence (PD) Plots")
    (description
     "Visualizes the main effects of individual predictor variables and their
second-order interaction effects in black-box supervised learning models.  The
package creates either Accumulated Local Effects (ALE) plots and/or Partial
Dependence (PD) plots, given a fitted supervised learning model.")
    (license license:gpl2)))

(define-public r-aldvmm
  (package
    (name "r-aldvmm")
    (version "0.8.5")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "aldvmm" version))
              (sha256
               (base32
                "1zmkzj0j7q26yvlinyc5z3papkvg57vziij5apwwpix0h9qpjq55"))))
    (properties `((upstream-name . "aldvmm")))
    (build-system r-build-system)
    (propagated-inputs (list r-optimr r-numderiv r-checkmate))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/pletschm/aldvmm/")
    (synopsis "Adjusted Limited Dependent Variable Mixture Models")
    (description
     "The goal of the package aldvmm is to fit adjusted limited dependent variable
mixture models of health state utilities.  Adjusted limited dependent variable
mixture models are finite mixtures of normal distributions with an accumulation
of density mass at the limits, and a gap between 100% quality of life and the
next smaller utility value.  The package aldvmm uses the likelihood and expected
value functions proposed by Hernandez Alava and Wailoo (2015)
<doi:10.1177/1536867X1501500307> using normal component distributions and a
multinomial logit model of probabilities of component membership.")
    (license license:gpl3)))

(define-public r-aldqr
  (package
    (name "r-aldqr")
    (version "1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ALDqr" version))
              (sha256
               (base32
                "0gk8hxh4p0fi47sf1zsvvxxbzp38vzk60wh8hmc63phnjab6qkv4"))))
    (properties `((upstream-name . "ALDqr")))
    (build-system r-build-system)
    (propagated-inputs (list r-sn r-hyperbolicdist))
    (home-page "https://cran.r-project.org/package=ALDqr")
    (synopsis "Quantile Regression Using Asymmetric Laplace Distribution")
    (description
     "EM algorithm for estimation of parameters and other methods in a quantile
regression.")
    (license license:gpl3+)))

(define-public r-ald
  (package
    (name "r-ald")
    (version "1.3.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ald" version))
              (sha256
               (base32
                "12nf9vakayw24clrg56fh9x85kg277iricbs8ymahkjqjnc1p3cz"))))
    (properties `((upstream-name . "ald")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=ald")
    (synopsis "The Asymmetric Laplace Distribution")
    (description
     "It provides the density, distribution function, quantile function, random number
generator, likelihood function, moments and Maximum Likelihood estimators for a
given sample, all this for the three parameter Asymmetric Laplace Distribution
defined in Koenker and Machado (1999).  This is a special case of the skewed
family of distributions available in Galarza et.al. (2017)
<doi:10.1002/sta4.140> useful for quantile regression.")
    (license license:gpl2+)))

(define-public r-albopictus
  (package
    (name "r-albopictus")
    (version "0.5")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "albopictus" version))
              (sha256
               (base32
                "0kw1agm9jqi9wl5zbx8bryngy751g3sih36rgbrx0m2170cy42d9"))))
    (properties `((upstream-name . "albopictus")))
    (build-system r-build-system)
    (home-page "https://github.com/kerguler/albopictusR")
    (synopsis "Age-Structured Population Dynamics Model")
    (description
     "This package implements discrete time deterministic and stochastic
age-structured population dynamics models described in Erguler and others (2016)
<doi:10.1371/journal.pone.0149282> and Erguler and others (2017)
<doi:10.1371/journal.pone.0174293>.")
    (license license:gpl3+)))

(define-public r-albatross
  (package
    (name "r-albatross")
    (version "0.3-5")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "albatross" version))
              (sha256
               (base32
                "153r9lmnf5mqy4i3i6ymqg57wvxyaf780zwzh0hm204v6v4l3nbq"))))
    (properties `((upstream-name . "albatross")))
    (build-system r-build-system)
    (propagated-inputs (list r-pracma r-multiway r-matrix r-lattice r-cmls))
    (home-page "https://cran.r-project.org/package=albatross")
    (synopsis "PARAFAC Analysis of Fluorescence Excitation-Emission Matrices")
    (description
     "Perform parallel factor analysis (PARAFAC: Hitchcock, 1927)
<doi:10.1002/sapm192761164> on fluorescence excitation-emission matrices: handle
scattering signal and inner filter effect, scale the dataset, fit the model;
perform split-half validation or jack-knifing.  Modified approaches such as
Whittaker interpolation, randomised split-half, and fluorescence and scattering
model estimation are also available.  The package has a low dependency footprint
and has been tested on a wide range of R versions.")
    (license license:gpl3+)))

(define-public r-alassosurvic
  (package
    (name "r-alassosurvic")
    (version "0.1.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ALassoSurvIC" version))
              (sha256
               (base32
                "0asaip7mq1brahirm025d57gk1fgysbmhi6jypf2jihai7dl4jg2"))))
    (properties `((upstream-name . "ALassoSurvIC")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpp))
    (home-page "https://cran.r-project.org/package=ALassoSurvIC")
    (synopsis
     "Adaptive Lasso for the Cox Regression with Interval Censored and Possibly Left Truncated Data")
    (description
     "Penalized variable selection tools for the Cox proportional hazards model with
interval censored and possibly left truncated data.  It performs variable
selection via penalized nonparametric maximum likelihood estimation with an
adaptive lasso penalty.  The optimal thresholding parameter can be searched by
the package based on the profile Bayesian information criterion (BIC).  The
asymptotic validity of the methodology is established in Li et al. (2019
<doi:10.1177/0962280219856238>).  The unpenalized nonparametric maximum
likelihood estimation for interval censored and possibly left truncated data is
also available.")
    (license license:gpl3+)))

(define-public r-alakazam
  (package
    (name "r-alakazam")
    (version "1.2.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "alakazam" version))
              (sha256
               (base32
                "1m4482haxw5cxkh5c39cr4smh9ldmv2anygnfswa4zc58slqf70n"))))
    (properties `((upstream-name . "alakazam")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-tibble
                             r-stringi
                             r-seqinr
                             r-scales
                             r-rlang
                             r-readr
                             r-rcpp
                             r-progress
                             r-matrix
                             r-iranges
                             r-igraph
                             r-ggplot2
                             r-genomicalignments
                             r-dplyr
                             r-biostrings
                             r-ape
                             r-airr))
    (native-inputs (list r-knitr))
    (home-page "https://alakazam.readthedocs.io/")
    (synopsis "Immunoglobulin Clonal Lineage and Diversity Analysis")
    (description
     "This package provides methods for high-throughput adaptive immune receptor
repertoire sequencing (AIRR-Seq; Rep-Seq) analysis.  In particular,
immunoglobulin (Ig) sequence lineage reconstruction, lineage topology analysis,
diversity profiling, amino acid property analysis and gene usage.  Citations:
Gupta and Vander Heiden, et al (2017) <doi:10.1093/bioinformatics/btv359>,
Stern, Yaari and Vander Heiden, et al (2014) <doi:10.1126/scitranslmed.3008879>.")
    (license license:agpl3)))

(define-public r-akmedoids
  (package
    (name "r-akmedoids")
    (version "1.3.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "akmedoids" version))
              (sha256
               (base32
                "19d9fh1cygn04riwc7y7lzdncyxki9rzikf9f5m96vp0y687z2ka"))))
    (properties `((upstream-name . "akmedoids")))
    (build-system r-build-system)
    (propagated-inputs (list r-signal
                             r-kml
                             r-hmisc
                             r-ggplot2
                             r-dplyr
                             r-clustercrit))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=akmedoids")
    (synopsis "Anchored Kmedoids for Longitudinal Data Clustering")
    (description
     "Advances a novel adaptation of longitudinal k-means clustering technique
(Genolini et al. (2015) <doi:10.18637/jss.v065.i04>) for grouping trajectories
based on the similarities of their long-term trends and determines the optimal
solution based on either the average silhouette width (Rousseeuw P. J. 1987) or
the Calinski-Harabatz criterion (Calinski and Harabatz (1974)
<doi:10.1080/03610927408827101>).  Includes functions to extract descriptive
statistics and generate a visualisation of the resulting groups, drawing methods
from the ggplot2 library (Wickham H. (2016) <doi:10.1007/978-3-319-24277-4>).
The package also includes a number of other useful functions for exploring and
manipulating longitudinal data prior to the clustering process.")
    (license license:gpl3)))

(define-public r-akmbiclust
  (package
    (name "r-akmbiclust")
    (version "0.1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "akmbiclust" version))
              (sha256
               (base32
                "19dj12vlry6f3agzrnshx2c4rpa2h7dlx2138r49jjy9sm48pyfw"))))
    (properties `((upstream-name . "akmbiclust")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=akmbiclust")
    (synopsis "Alternating K-Means Biclustering")
    (description
     "This package implements the alternating k-means biclustering algorithm in
Fraiman and Li (2020) <arXiv:2009.04550>.")
    (license license:gpl3)))

(define-public r-akima
  (package
    (name "r-akima")
    (version "0.6-3.4")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "akima" version))
              (sha256
               (base32
                "0gmdh5kvq455k82pvdsqbkk69bi7g0960jq5rcl3cbhxm297arcm"))))
    (properties `((upstream-name . "akima")))
    (build-system r-build-system)
    (propagated-inputs (list r-sp))
    (native-inputs (list gfortran))
    (home-page "https://cran.r-project.org/package=akima")
    (synopsis "Interpolation of Irregularly and Regularly Spaced Data")
    (description
     "Several cubic spline interpolation methods of H. Akima for irregular and regular
gridded data are available through this package, both for the bivariate case
(irregular data: ACM 761, regular data: ACM 760) and univariate case (ACM 433
and ACM 697).  Linear interpolation of irregular gridded data is also covered by
reusing D. J. Renkas triangulation code which is part of Akimas Fortran code.  A
bilinear interpolator for regular grids was also added for comparison with the
bicubic interpolator on regular grids.")
    (license (list (license:fsdg-compatible "ACM")
                   (license:fsdg-compatible "file://LICENSE")))))

(define-public r-akiflagger
  (package
    (name "r-akiflagger")
    (version "0.3.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "akiFlagger" version))
              (sha256
               (base32
                "08z5jvigzvl3af17dd8l6zil0s694i22x0a7xvb3n4fvg6fargz4"))))
    (properties `((upstream-name . "akiFlagger")))
    (build-system r-build-system)
    (propagated-inputs (list r-zoo r-shiny r-dplyr r-data-table))
    (home-page "https://github.com/isaranwrap/akiFlagger")
    (synopsis "Flags Acute Kidney Injury (AKI)")
    (description
     "Flagger to detect acute kidney injury (AKI) in a patient dataset.")
    (license license:expat)))

(define-public r-ake
  (package
    (name "r-ake")
    (version "1.0.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "Ake" version))
              (sha256
               (base32
                "0mdpx1dnk57yr0mpf9hqqdjx96j0sqdjdy964qvwmqbycvxxnp3z"))))
    (properties `((upstream-name . "Ake")))
    (build-system r-build-system)
    (home-page "www.r-project.org")
    (synopsis "Associated Kernel Estimations")
    (description
     "Continuous and discrete (count or categorical) estimation of density,
probability mass function (p.m.f.) and regression functions are performed using
associated kernels.  The cross-validation technique and the local Bayesian
procedure are also implemented for bandwidth selection.")
    (license license:gpl2+)))

(define-public r-akc
  (package
    (name "r-akc")
    (version "0.9.8.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "akc" version))
              (sha256
               (base32
                "0prqvjbcm9aagjhxpzidi2jr2yddzqwqrwp5rm3ki8215fwr9mln"))))
    (properties `((upstream-name . "akc")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidytext
                             r-tidygraph
                             r-tidyfst
                             r-tibble
                             r-textstem
                             r-stringr
                             r-rlang
                             r-magrittr
                             r-igraph
                             r-ggwordcloud
                             r-ggraph
                             r-ggplot2
                             r-ggforce
                             r-dplyr
                             r-data-table))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/hope-data-science/akc")
    (synopsis "Automatic Knowledge Classification")
    (description
     "This package provides a tidy framework for automatic knowledge classification
and visualization.  Currently, the core functionality of the framework is mainly
supported by modularity-based clustering (community detection) in keyword
co-occurrence network, and focuses on co-word analysis of bibliometric research.
 However, the designed functions in akc are general, and could be extended to
solve other tasks in text mining as well.")
    (license license:expat)))

(define-public r-ajv
  (package
    (name "r-ajv")
    (version "1.0.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ajv" version))
              (sha256
               (base32
                "1qd5ncb7rdnnvqfknsvq9nrpxrh0zv3jyh4b91dcvfvhp262vfrm"))))
    (properties `((upstream-name . "ajv")))
    (build-system r-build-system)
    (propagated-inputs (list r-yaml r-v8 r-rjsonio))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/jdthorpe/ajvr")
    (synopsis "Another JSON Schema Validator")
    (description
     "This package provides a thin wrapper around the ajv JSON validation package for
JavaScript.  See <http://epoberezkin.github.io/ajv/> for details.")
    (license license:gpl2)))

(define-public r-aisoph
  (package
    (name "r-aisoph")
    (version "0.2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "aisoph" version))
              (sha256
               (base32
                "1c64slva2yb3phflxslxbpp4iydxx92hrj9xi7dv1bsbag8n9xd7"))))
    (properties `((upstream-name . "aisoph")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival r-rcpp r-iso))
    (home-page "https://cran.r-project.org/package=aisoph")
    (synopsis "Additive Isotonic Proportional Hazards Model")
    (description
     "Nonparametric estimation of additive isotonic covariate effects for proportional
hazards model.")
    (license license:gpl2+)))

(define-public r-airthermo
  (package
    (name "r-airthermo")
    (version "1.2.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "aiRthermo" version))
              (sha256
               (base32
                "058082qdfi1pbdgf26vbfahri1kbc8b2l816q4dq89j5aj5is0a2"))))
    (properties `((upstream-name . "aiRthermo")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=aiRthermo")
    (synopsis "Atmospheric Thermodynamics and Visualization")
    (description
     "Deals with many computations related to the thermodynamics of atmospheric
processes.  It includes many functions designed to consider the density of air
with varying degrees of water vapour in it, saturation pressures and mixing
ratios, conversion of moisture indices, computation of atmospheric states of
parcels subject to dry or pseudoadiabatic vertical evolutions and atmospheric
instability indices that are routinely used for operational weather forecasts or
meteorological diagnostics.")
    (license license:gpl3)))

(define-public r-airt
  (package
    (name "r-airt")
    (version "0.2.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "airt" version))
              (sha256
               (base32
                "1az5fd9zr6lgmcim4v6rzckl9yyw9myvhmzs76n71864gnzkbna4"))))
    (properties `((upstream-name . "airt")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-tibble
                             r-rlang
                             r-pracma
                             r-mirt
                             r-magrittr
                             r-estcrm
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://sevvandi.github.io/airt/")
    (synopsis "Evaluation of Algorithm Collections Using Item Response Theory")
    (description
     "An evaluation framework for algorithm portfolios using Item Response Theory
(IRT).  We use continuous and polytomous IRT models to evaluate algorithms and
introduce algorithm characteristics such as stability, effectiveness and
anomalousness (Kandanaarachchi, Smith-Miles 2020)
<doi:10.13140/RG.2.2.11363.09760>.")
    (license license:gpl3)))

(define-public r-airr
  (package
    (name "r-airr")
    (version "1.4.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "airr" version))
              (sha256
               (base32
                "1zr8nzhy75v82sk1lxp8xk34hxz84zjk9nrgx10kzrycpyrbfjw0"))))
    (properties `((upstream-name . "airr")))
    (build-system r-build-system)
    (propagated-inputs (list r-yaml r-stringi r-readr r-jsonlite))
    (native-inputs (list r-knitr))
    (home-page "http://docs.airr-community.org")
    (synopsis "AIRR Data Representation Reference Library")
    (description
     "Schema definitions and read, write and validation tools for data formatted in
accordance with the AIRR Data Representation schemas defined by the AIRR
Community <http://docs.airr-community.org>.")
    (license (license:fsdg-compatible "CC BY 4.0"))))

(define-public r-airqualityes
  (package
    (name "r-airqualityes")
    (version "1.0.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "airqualityES" version))
              (sha256
               (base32
                "1kf673ajk06ggy9524lip5flpfgq0gql7d46kgnri8l3kbzw7zcj"))))
    (properties `((upstream-name . "airqualityES")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble))
    (home-page "https://github.com/jdieramon/airqualityES")
    (synopsis "Air Quality Measurements in Spain from 2011 to 2018")
    (description
     "These dataset contains daily quality air measurements in Spain over a period of
18 years (from 2001 to 2018).  The measurements refer to several pollutants.
These data are openly published by the Government of Spain.  The datasets were
originally spread over a number of files and formats.  Here, the same
information is contained in simple dataframe for convenience of researches,
journalists or general public.  See the Spanish Government website
<http://www.miteco.gob.es/> for more information.")
    (license license:cc-by-sa4.0)))

(define-public r-airports
  (package
    (name "r-airports")
    (version "0.1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "airports" version))
              (sha256
               (base32
                "1ahfqqfcvr731hj0h7d00jd87h1adiryh42sv4mh318lk5rglm6f"))))
    (properties `((upstream-name . "airports")))
    (build-system r-build-system)
    (home-page "https://github.com/OpenIntroStat/airports")
    (synopsis "Data on Airports")
    (description "Geographic, use, and property related data on airports.")
    (license license:gpl3)))

(define-public r-airportr
  (package
    (name "r-airportr")
    (version "0.1.3")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "airportr" version))
              (sha256
               (base32
                "1h8h0cdfqgxv8cf9hp82sx5n4a1z88qyyxicj7d2kmmybqqz2r5n"))))
    (properties `((upstream-name . "airportr")))
    (build-system r-build-system)
    (propagated-inputs (list r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/dshkol/airportr")
    (synopsis "Convenience Tools for Working with Airport Data")
    (description
     "Retrieves open source airport data and provides tools to look up information,
translate names into codes and vice-verse, as well as some basic calculation
functions for measuring distances.  Data is licensed under the Open Database
License.")
    (license license:expat)))

(define-public r-airnow
  (package
    (name "r-airnow")
    (version "0.1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "airnow" version))
              (sha256
               (base32
                "0dpx2hkh0y6769pi8xzyi327lygxysckqz85z40ps50ghw02r8bh"))))
    (properties `((upstream-name . "airnow")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble
                             r-rlang
                             r-lifecycle
                             r-jsonlite
                             r-httr2
                             r-glue
                             r-cli))
    (home-page "https://github.com/briandconnelly/airnow")
    (synopsis "Retrieve 'AirNow' Air Quality Observations and Forecasts")
    (description
     "Retrieve air quality data via the AirNow <https://www.airnow.gov/> API.")
    (license license:expat)))

(define-public r-airmonitor
  (package
    (name "r-airmonitor")
    (version "0.2.2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AirMonitor" version))
              (sha256
               (base32
                "1pjr0cv8p4wh1r42dclarxbbd4iiwrv8zn6igdkr19829k1airkw"))))
    (properties `((upstream-name . "AirMonitor")))
    (build-system r-build-system)
    (propagated-inputs (list r-xts
                             r-tidyselect
                             r-stringr
                             r-rlang
                             r-readr
                             r-mazamatimeseries
                             r-mazamacoreutils
                             r-magrittr
                             r-lubridate
                             r-leaflet
                             r-dygraphs
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/MazamaScience/AirMonitor")
    (synopsis "Air Quality Data Analysis")
    (description
     "Utilities for working with hourly air quality monitoring data with a focus on
small particulates (PM2.5).  A compact data model is structured as a list with
two dataframes.  A meta dataframe contains spatial and measuring device metadata
associated with deployments at known locations.  A data dataframe contains a
datetime column followed by columns of measurements associated with each
\"device-deployment\".  Algorithms to calculate NowCast and the associated Air
Quality Index (AQI) are defined at the US Environmental Projection Agency AirNow
program:
<https://www.airnow.gov/sites/default/files/2020-05/aqi-technical-assistance-document-sept2018.pdf>.")
    (license license:gpl3)))

(define-public r-airly
  (package
    (name "r-airly")
    (version "0.1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "aiRly" version))
              (sha256
               (base32
                "0d3w5dwk0b3pd49zw2005rili4p3l1i3x4hzp8cf6rljr86x01cy"))))
    (properties `((upstream-name . "aiRly")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble r-reshape2 r-jsonlite r-httr))
    (home-page "https://github.com/piotrekjanus/aiRly")
    (synopsis "R Wrapper for 'Airly' API")
    (description
     "Get information about air quality using Airly <https://airly.eu/> API through R.")
    (license license:expat)))

(define-public r-airgrteaching
  (package
    (name "r-airgrteaching")
    (version "0.2.13")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "airGRteaching" version))
              (sha256
               (base32
                "1j95b1rz83f1x8gp6107rdk9g81j47yhgdlf8y17f0ffgrvwwfky"))))
    (properties `((upstream-name . "airGRteaching")))
    (build-system r-build-system)
    (propagated-inputs (list r-xts
                             r-shinyjs
                             r-shiny
                             r-plotrix
                             r-markdown
                             r-dygraphs
                             r-airgr))
    (native-inputs (list r-knitr))
    (home-page "https://hydrogr.github.io/airGRteaching/")
    (synopsis
     "Teaching Hydrological Modelling with the GR Rainfall-Runoff Models ('Shiny' Interface Included)")
    (description
     "Add-on package to the airGR package that simplifies its use and is aimed at
being used for teaching hydrology.  The package provides 1) three functions that
allow to complete very simply a hydrological modelling exercise 2) plotting
functions to help students to explore observed data and to interpret the results
of calibration and simulation of the GR ('Génie rural') models 3) a Shiny
graphical interface that allows for displaying the impact of model parameters on
hydrographs and models internal variables.")
    (license license:gpl2)))

(define-public r-airgriwrm
  (package
    (name "r-airgriwrm")
    (version "0.6.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "airGRiwrm" version))
              (sha256
               (base32
                "1dr7xg8a6xfdihmf4x03wm268iz78lks15fx9hmpw6sp15xv5kdj"))))
    (properties `((upstream-name . "airGRiwrm")))
    (build-system r-build-system)
    (propagated-inputs (list r-dplyr r-diagrammer r-airgr))
    (native-inputs (list r-knitr))
    (home-page "https://airgriwrm.g-eau.fr/")
    (synopsis "'airGR' Integrated Water Resource Management")
    (description
     "Semi-distributed Precipitation-Runoff Modelling based on airGR package models
integrating human infrastructures and their managements.")
    (license license:agpl3)))

(define-public r-airgrdatassim
  (package
    (name "r-airgrdatassim")
    (version "0.1.3")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "airGRdatassim" version))
              (sha256
               (base32
                "05c108rcj4rlzrbabai95abxhyjsrrrsgvds4zamvyzpjl64f9ps"))))
    (properties `((upstream-name . "airGRdatassim")))
    (build-system r-build-system)
    (propagated-inputs (list r-airgr))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=airGRdatassim")
    (synopsis "Ensemble-Based Data Assimilation with GR Hydrological Models")
    (description
     "Add-on to the airGR package which provides the tools to assimilate observed
discharges in daily GR hydrological models.  The package consists in two
functions allowing to perform the assimilation of observed discharges via the
Ensemble Kalman filter or the Particle filter as described in Piazzi et al.
(2021) <doi:10.1029/2020WR028390>.")
    (license license:gpl2)))

(define-public r-airgr
  (package
    (name "r-airgr")
    (version "1.7.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "airGR" version))
              (sha256
               (base32
                "0miqkhapw3ch4wss8dkygf5j5rj9jwdm7xdb4c5jfdnxdbbsxwjs"))))
    (properties `((upstream-name . "airGR")))
    (build-system r-build-system)
    (native-inputs (list r-knitr gfortran))
    (home-page "https://hydrogr.github.io/airGR/")
    (synopsis
     "Suite of GR Hydrological Models for Precipitation-Runoff Modelling")
    (description
     "Hydrological modelling tools developed at INRAE-Antony (HYCAR Research Unit,
France).  The package includes several conceptual rainfall-runoff models (GR4H,
GR5H, GR4J, GR5J, GR6J, GR2M, GR1A) that can be applied either on a lumped or
semi-distributed way.  A snow accumulation and melt model (CemaNeige) and the
associated functions for the calibration and evaluation of models are also
included.  Use help(airGR) for package description and references.")
    (license license:gpl2)))

(define-public r-aire-zmvm
  (package
    (name "r-aire-zmvm")
    (version "0.8.2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "aire.zmvm" version))
              (sha256
               (base32
                "0z9knqdl7ihx2vph154qi1lh4s6yvlcw6kwry8k47mhh3p7pynsd"))))
    (properties `((upstream-name . "aire.zmvm")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml2
                             r-tidyr
                             r-stringr
                             r-sp
                             r-rvest
                             r-readxl
                             r-readr
                             r-progress
                             r-lubridate
                             r-httr
                             r-dplyr))
    (home-page "https://hoyodesmog.diegovalle.net/aire.zmvm/")
    (synopsis "Download Mexico City Pollution, Wind, and Temperature Data")
    (description
     "Tools for downloading hourly averages, daily maximums and minimums from each of
the pollution, wind, and temperature measuring stations or geographic zones in
the Mexico City metro area.  The package also includes the locations of each of
the stations and zones.  See <http://aire.cdmx.gob.mx/> for more information.")
    (license license:bsd-3)))

(define-public r-aipw
  (package
    (name "r-aipw")
    (version "0.6.3.2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AIPW" version))
              (sha256
               (base32
                "1iqq665qigw9dmc62x2dz1nvrk8s65ph0a3k2p7mkznr9frshhi2"))))
    (properties `((upstream-name . "AIPW")))
    (build-system r-build-system)
    (propagated-inputs (list r-superlearner
                             r-rsolnp
                             r-r6
                             r-progressr
                             r-ggplot2
                             r-future-apply))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/yqzhong7/AIPW")
    (synopsis "Augmented Inverse Probability Weighting")
    (description
     "The AIPW pacakge implements the augmented inverse probability weighting, a
doubly robust estimator, for average causal effect estimation with user-defined
stacked machine learning algorithms.  To cite the AIPW package, please use:
\"Yongqi Zhong, Edward H. Kennedy, Lisa M. Bodnar, Ashley I. Naimi (2021, In
Press).  AIPW: An R Package for Augmented Inverse Probability Weighted
Estimation of Average Causal Effects.  American Journal of Epidemiology\".
Visit: <https://yqzhong7.github.io/AIPW/> for more information.")
    (license license:gpl3)))

(define-public r-aimsir17
  (package
    (name "r-aimsir17")
    (version "0.0.2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "aimsir17" version))
              (sha256
               (base32
                "0v804maqaygqhw3y9wqap3h9vvjniqnnbsv1psjj500r2yscicxs"))))
    (properties `((upstream-name . "aimsir17")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble))
    (home-page "https://github.com/JimDuggan/aimsir17")
    (synopsis "Irish Weather Observing Stations Hourly Records for 2017")
    (description
     "Named after the Irish name for weather, this package contains tidied data from
the Irish Meteorological Service's hourly observations for 2017.  In all, the
data sets include observations from 25 weather stations, and also latitude and
longitude coordinates for each weather station.  Now includes energy generation
data for Ireland and Northern Ireland (2017), including Wind Generation data.")
    (license (license:fsdg-compatible
              "Creative Commons Attribution 4.0 International License"))))

(define-public r-aimplot
  (package
    (name "r-aimplot")
    (version "1.0.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "aimPlot" version))
              (sha256
               (base32
                "1d52b7kccxba6j7n0gbd7pzs0p87zn32vv8gdf2f7lyr75qzgz7x"))))
    (properties `((upstream-name . "aimPlot")))
    (build-system r-build-system)
    (propagated-inputs (list r-ggplot2))
    (home-page "https://cran.r-project.org/package=aimPlot")
    (synopsis "Create Pie Like Plot for Completeness")
    (description
     "Create a pie like plot to visualise if the aim or several aims of a project is
achieved or close to be achieved i.e the aim is achieved when the point is at
the center of the pie plot.  Imagine it's like a dartboard and the center means
100% completeness/achievement.  Achievement can also be understood as 100%
coverage.  The standard distribution of completeness allocated in the pie plot
is 50%, 80% and 100% completeness.")
    (license license:gpl2)))

(define-public r-aig
  (package
    (name "r-aig")
    (version "0.1.9")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AIG" version))
              (sha256
               (base32
                "1jnnfmcwxcv4fsdcz7jb2lgczxdwrq3qxg2bhsh1610iwz4gzii7"))))
    (properties `((upstream-name . "AIG")))
    (build-system r-build-system)
    (propagated-inputs (list r-rgl r-mgcv r-magrittr r-dplyr))
    (home-page "https://cran.r-project.org/package=AIG")
    (synopsis "Automatic Item Generator")
    (description
     "This package provides a collection of Automatic Item Generators used mainly for
psychological research.  This package can generate linear syllogistic reasoning,
arithmetic and 2D/3D/Double 3D spatial reasoning items.  It is recommended for
research purpose only.")
    (license license:gpl3)))

(define-public r-aif360
  (package
    (name "r-aif360")
    (version "0.1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "aif360" version))
              (sha256
               (base32
                "0r9x9q8kc9alk1j3p0y23ispcbfac89q0c043vh8dw89q267plf8"))))
    (properties `((upstream-name . "aif360")))
    (build-system r-build-system)
    (propagated-inputs (list r-rstudioapi r-reticulate))
    (home-page "https://github.com/IBM/AIF360/tree/master/aif360/aif360-r")
    (synopsis "Help Detect and Mitigate Bias in Machine Learning Models")
    (description
     "The AI Fairness 360 <https://aif360.mybluemix.net/> toolkit is an open-source
library to help detect and mitigate bias in machine learning models.  The AI
Fairness 360 R package includes a comprehensive set of metrics for datasets and
models to test for biases, explanations for these metrics, and algorithms to
mitigate bias in datasets and models.")
    (license (license:fsdg-compatible "Apache License (>= 2.0)"))))

(define-public r-aidar
  (package
    (name "r-aidar")
    (version "1.0.5")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "aidar" version))
              (sha256
               (base32
                "1q2iz2qzh2yl0v0sc537xq4vbx2nblym3kv419vr7jvrghdpx3vj"))))
    (properties `((upstream-name . "aidar")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml))
    (home-page "https://cran.r-project.org/package=aidar")
    (synopsis "Tools for Reading AIDA Files")
    (description
     "Read objects from the AIDA (<http://aida.freehep.org/>) file and make them
available as dataframes in R.")
    (license license:lgpl2.0+)))

(define-public r-aid
  (package
    (name "r-aid")
    (version "2.7")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AID" version))
              (sha256
               (base32
                "0zcch4vnl1v4xlgh8rf31b3d8dxxdk2cbv5pv9al79w1g46q16yn"))))
    (properties `((upstream-name . "AID")))
    (build-system r-build-system)
    (propagated-inputs (list r-tseries
                             r-stringr
                             r-psych
                             r-nortest
                             r-meta
                             r-mass
                             r-ggplot2))
    (home-page "https://cran.r-project.org/package=AID")
    (synopsis "Box-Cox Power Transformation")
    (description
     "This package performs Box-Cox power transformation for different purposes,
graphical approaches, assesses the success of the transformation via tests and
plots, computes mean and confidence interval for back transformed data.")
    (license license:gpl2+)))

(define-public r-aiccmodavg
  (package
    (name "r-aiccmodavg")
    (version "2.3-1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AICcmodavg" version))
              (sha256
               (base32
                "1c2qqizssy7jvzkndlljazk28rjq5csgawzs43gv3s9qbahpslfh"))))
    (properties `((upstream-name . "AICcmodavg")))
    (build-system r-build-system)
    (propagated-inputs (list r-xtable
                             r-vgam
                             r-unmarked
                             r-survival
                             r-nlme
                             r-matrix
                             r-mass
                             r-lattice))
    (home-page "https://cran.r-project.org/package=AICcmodavg")
    (synopsis "Model Selection and Multimodel Inference Based on (Q)AIC(c)")
    (description
     "This package provides functions to implement model selection and multimodel
inference based on Akaike's information criterion (AIC) and the second-order AIC
(AICc), as well as their quasi-likelihood counterparts (QAIC, QAICc) from
various model object classes.  The package implements classic model averaging
for a given parameter of interest or predicted values, as well as a shrinkage
version of model averaging parameter estimates or effect sizes.  The package
includes diagnostics and goodness-of-fit statistics for certain model types
including those of unmarkedFit classes estimating demographic parameters after
accounting for imperfect detection probabilities.  Some functions also allow the
creation of model selection tables for Bayesian models of the bugs', rjags', and
jagsUI classes.  Functions also implement model selection using BIC. Objects
following model selection and multimodel inference can be formatted to LaTeX
using xtable methods included in the package.")
    (license license:gpl2+)))

(define-public r-aic
  (package
    (name "r-aic")
    (version "1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "aIc" version))
              (sha256
               (base32
                "1w2rvw1kc4a9b2mi3bh10siv3j89xb3qrx7nydw4kqrgi5c4v3i4"))))
    (properties `((upstream-name . "aIc")))
    (build-system r-build-system)
    (propagated-inputs (list r-zcompositions
                             r-vegan
                             r-shiny
                             r-matrixcalc
                             r-edger
                             r-aldex2))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/ggloor/aIc")
    (synopsis "Testing for Compositional Pathologies in Datasets")
    (description
     "This package provides a set of tests for compositional pathologies.  Tests for
coherence of correlations with aIc.coherent() as suggested by (Erb et al. (2020)
<doi:10.1016/j.acags.2020.100026>), compositional dominance of distance with
aIc.dominant(), compositional perturbation invariance with aIc.perturb() as
suggested by (Aitchison (1992) <doi:10.1007/BF00891269>) and singularity of the
covariation matrix with aIc.singular().  Currently tests five data
transformations: prop, clr, TMM, TMMwsp, and RLE from the R packages ALDEx2',
edgeR and DESeq2 (Fernandes et al (2014) <doi:10.1186/2049-2618-2-15>, Anders et
al. (2013)<doi:10.1038/nprot.2013.099>).")
    (license license:gpl3+)))

(define-public r-aibd
  (package
    (name "r-aibd")
    (version "0.1.9")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "aibd" version))
              (sha256
               (base32
                "1ispw8y0k665fdpw1c0swmhzl596jr89lnwyq741ak6ic92s3pzz"))))
    (properties `((upstream-name . "aibd")))
    (build-system r-build-system)
    (propagated-inputs (list r-rscala r-commonsmath))
    (home-page "https://cran.r-project.org/package=aibd")
    (synopsis "Attraction Indian Buffet Distribution")
    (description
     "An implementation of probability mass function and sampling algorithms is
provided for the attraction Indian buffet distribution (AIBD), originally from
Dahl (2016)
<https://ww2.amstat.org/meetings/jsm/2016/onlineprogram/ActivityDetails.cfm?SessionID=213038>.")
    (license license:gpl3)))

(define-public r-ahsurv
  (package
    (name "r-ahsurv")
    (version "0.1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AHSurv" version))
              (sha256
               (base32
                "051q6iamqhhkrq7bfhq40n9svd4wfqyxscgwfnsflqdmbgm6gghs"))))
    (properties `((upstream-name . "AHSurv")))
    (build-system r-build-system)
    (propagated-inputs (list r-rootsolve r-flexsurv))
    (home-page "https://cran.r-project.org/package=AHSurv")
    (synopsis "Flexible Parametric Accelerated Hazards Models")
    (description
     "Flexible parametric Accelerated Hazards (AH) regression models in overall and
relative survival frameworks with 13 distinct Baseline Distributions.  The AH
Model can also be applied to lifetime data with crossed survival curves.  Any
user-defined parametric distribution can be fitted, given at least an R function
defining the cumulative hazard and hazard rate functions.  See Chen and Wang
(2000) <doi:10.1080/01621459.2000.10474236>, and Lee (2015)
<doi:10.1007/s10985-015-9349-5> for more details.")
    (license license:gpl3)))

(define-public r-ahptopsis2n
  (package
    (name "r-ahptopsis2n")
    (version "0.2.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ahptopsis2n" version))
              (sha256
               (base32
                "0pjxchrjik0d3ydr1hjqrba1p1y9sirwjwzjkmxh2fk803c0b9la"))))
    (properties `((upstream-name . "ahptopsis2n")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=ahptopsis2n")
    (synopsis "Hybrid Method for Multiple Criteria Decision-Making (MCDM)")
    (description
     "Implementation of a hybrid MCDM method build from the AHP (Analytic Hierarchy
Process) and TOPSIS-2N (Technique for Order of Preference by Similarity to Ideal
Solution - with two normalizations).  This method is described in Souza et al.
(2018) <doi: 10.1142/S0219622018500207>.")
    (license license:gpl3)))

(define-public r-ahpsurvey
  (package
    (name "r-ahpsurvey")
    (version "0.4.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ahpsurvey" version))
              (sha256
               (base32
                "1r7x4c318nzbx0ppm9272kfpz2bln1cafkv9irnj85nsdcravr33"))))
    (properties `((upstream-name . "ahpsurvey")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-rdpack
                             r-randomnames
                             r-magrittr
                             r-knitr
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=ahpsurvey")
    (synopsis "Analytic Hierarchy Process for Survey Data")
    (description
     "The Analytic Hierarchy Process is a versatile multi-criteria decision-making
tool introduced by Saaty (1987) <doi:10.1016/0270-0255(87)90473-8> that allows
decision-makers to weigh attributes and evaluate alternatives presented to them.
 This package provides a consistent methodology for researchers to reformat data
and run analytic hierarchy process in R on data that are formatted using the
survey data entry mode.  It is optimized for performing the analytic hierarchy
process with many decision-makers, and provides tools and options for
researchers to aggregate individual preferences and test multiple options.  It
also allows researchers to quantify, visualize and correct for inconsistency in
the decision-maker's comparisons.")
    (license license:expat)))

(define-public r-ahphybrid
  (package
    (name "r-ahphybrid")
    (version "0.1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AHPhybrid" version))
              (sha256
               (base32
                "1hf2ba52nim13jwkq857vnmnnb1yhgdz6kipqg3mmqrgz7kg52v1"))))
    (properties `((upstream-name . "AHPhybrid")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=AHPhybrid")
    (synopsis "AHP Hybrid Method")
    (description
     "The AHP method (Analytic Hierarchy Process) is a multi-criteria decision-making
method addressing choice and outranking problems.  The method enables to perform
the analysis of alternatives in each type of criterion and then provides a
global performance of each alternative in the decision context.  The main
difference of this package is the possibility of evaluating the alternatives
using quantitative data, by numerical representation, and qualitative data,
using the Saaty scale, providing preference relation between variables by a
pairwise evaluation.")
    (license license:gpl3)))

(define-public r-ahocorasicktrie
  (package
    (name "r-ahocorasicktrie")
    (version "0.1.2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AhoCorasickTrie" version))
              (sha256
               (base32
                "0zh3y5jd8m0xbj6lqr01zvwj9qd1xr3iq7vd6sgr3g3qh4kqm5pq"))))
    (properties `((upstream-name . "AhoCorasickTrie")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpp))
    (home-page "https://github.com/chambm/AhoCorasickTrie")
    (synopsis "Fast Searching for Multiple Keywords in Multiple Texts")
    (description
     "Aho-Corasick is an optimal algorithm for finding many keywords in a text.  It
can locate all matches in a text in O(N+M) time; i.e., the time needed scales
linearly with the number of keywords (N) and the size of the text (M).  Compare
this to the naive approach which takes O(N*M) time to loop through each pattern
and scan for it in the text.  This implementation builds the trie (the generic
name of the data structure) and runs the search in a single function call.  If
you want to search multiple texts with the same trie, the function will take a
list or vector of texts and return a list of matches to each text.  By default,
all 128 ASCII characters are allowed in both the keywords and the text.  A more
efficient trie is possible if the alphabet size can be reduced.  For example,
DNA sequences use at most 19 distinct characters and usually only 4; protein
sequences use at most 26 distinct characters and usually only 20.  UTF-8
(Unicode) matching is not currently supported.")
    (license license:asl2.0)))

(define-public r-ahnr
  (package
    (name "r-ahnr")
    (version "0.3.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ahnr" version))
              (sha256
               (base32
                "1g8m3q108ricfyn4fjjaihpr93xz7fm2sfzg3i0fz1n1i703jwm8"))))
    (properties `((upstream-name . "ahnr")))
    (build-system r-build-system)
    (propagated-inputs (list r-visnetwork
                             r-purrr
                             r-pracma
                             r-pdist
                             r-matrixcalc
                             r-magrittr
                             r-ggplot2))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/jroberayalas/ahnr")
    (synopsis "An Implementation of the Artificial Hydrocarbon Networks")
    (description
     "Implementation of the Artificial Hydrocarbon Networks for data modeling.")
    (license (list license:gpl3
                   (license:fsdg-compatible "file://LICENSE")))))

(define-public r-ahmle
  (package
    (name "r-ahmle")
    (version "1.20.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ahMLE" version))
              (sha256
               (base32
                "1phfzl0kynrq1if12h736jdxrfqc3i4kd32hp7sy2k2z7hkj1dkm"))))
    (properties `((upstream-name . "ahMLE")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival r-rcpparmadillo r-rcpp r-matrix
                             r-invgauss))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=ahMLE")
    (synopsis "Methods for the Additive Hazard Model")
    (description
     "This package provides methods for fitting additive hazards model.  Perform the
maximum likelihood method as well as the traditional Aalen's method for
estimating the additive hazards model.  For details see Chengyuan Lu(2021)
<arXiv:2004.06156>.")
    (license license:gpl2+)))

(define-public r-ahmbook
  (package
    (name "r-ahmbook")
    (version "0.2.6")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AHMbook" version))
              (sha256
               (base32
                "055li8mj863icvcrp23wfsg7gf8zmi8zn0hck2yraygazv2xk97k"))))
    (properties `((upstream-name . "AHMbook")))
    (build-system r-build-system)
    (propagated-inputs (list r-unmarked
                             r-spdep
                             r-sp
                             r-raster
                             r-plotrix
                             r-mvtnorm
                             r-fields
                             r-coda))
    (home-page
     "https://sites.google.com/site/appliedhierarchicalmodeling/home")
    (synopsis
     "Functions and Data for the Book 'Applied Hierarchical Modeling in Ecology' Vols 1 and 2")
    (description
     "This package provides functions to simulate data sets from hierarchical
ecological models, including all the simulations described in the two volume
publication Applied Hierarchical Modeling in Ecology: Analysis of distribution,
abundance and species richness in R and BUGS by Marc Kéry and Andy Royle:
volume 1 (2016, ISBN: 978-0-12-801378-6) and volume 2 (2021, ISBN:
978-0-12-809585-0), <https://www.mbr-pwrc.usgs.gov/pubanalysis/keryroylebook/>.
It also has all the utility functions and data sets needed to replicate the
analyses shown in the books.")
    (license license:gpl3+)))

(define-public r-ahm
  (package
    (name "r-ahm")
    (version "1.0.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AHM" version))
              (sha256
               (base32
                "00r1rn7d64a18rckbxvla5yapqv00p9ajxv72fx7s6p80kfal89w"))))
    (properties `((upstream-name . "AHM")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-tibble
                             r-quadprog
                             r-plgp
                             r-mixexp
                             r-matrix
                             r-glmnet
                             r-dplyr
                             r-devtools))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=AHM")
    (synopsis
     "Additive Heredity Model: Method for the Mixture-of-Mixtures Experiments")
    (description
     "An implementation of the additive heredity model for the mixture-of-mixtures
experiments of Shen et al. (2019) in Technometrics
<doi:10.1080/00401706.2019.1630010>.  The additive heredity model considers an
additive structure to inherently connect the major components with the minor
components.  The additive heredity model has a meaningful interpretation for the
estimated model because of the hierarchical and heredity principles applied and
the nonnegative garrote technique used for variable selection.")
    (license license:gpl3)))

(define-public r-ahaz
  (package
    (name "r-ahaz")
    (version "1.15")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ahaz" version))
              (sha256
               (base32
                "0k6i8s2miic2y1dgwjlpkhmaw6k3phn772p0600gcnjqxbqajznh"))))
    (properties `((upstream-name . "ahaz")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival r-matrix))
    (home-page "https://cran.r-project.org/package=ahaz")
    (synopsis "Regularization for Semiparametric Additive Hazards Regression")
    (description
     "Computationally efficient procedures for regularized estimation with the
semiparametric additive hazards regression model.")
    (license license:gpl2)))

(define-public r-agvgd
  (package
    (name "r-agvgd")
    (version "0.1.2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "agvgd" version))
              (sha256
               (base32
                "0b3wvxrp77b180pm8asih88cyh4vf2yjj7rvl0f02x28a0ia0xki"))))
    (properties `((upstream-name . "agvgd")))
    (build-system r-build-system)
    (propagated-inputs (list r-vctrs
                             r-tidyr
                             r-tibble
                             r-stringr
                             r-seqinr
                             r-rlang
                             r-purrr
                             r-magrittr
                             r-grantham
                             r-glue
                             r-dplyr
                             r-crayon))
    (home-page "https://maialab.org/agvgd/")
    (synopsis "An R Implementation of the 'Align-GVGD' Method")
    (description
     "Align-GVGD ('A-GVGD') is a method to predict the impact of missense
substitutions based on the properties of amino acid side chains and protein
multiple sequence alignments <doi:10.1136/jmg.2005.033878>.  A-GVGD is an
extension of the original Grantham distance to multiple sequence alignments.
This package provides an alternative R implementation to the web version found
on <http://agvgd.hci.utah.edu/>.")
    (license license:expat)))

(define-public r-agua
  (package
    (name "r-agua")
    (version "0.1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "agua" version))
              (sha256
               (base32
                "0hqzb88dv9iha2c12fbahvd2n2jrsjsjv00y2dnwv27rv354vj9y"))))
    (properties `((upstream-name . "agua")))
    (build-system r-build-system)
    (propagated-inputs (list r-workflows
                             r-vctrs
                             r-tune
                             r-tidyr
                             r-tibble
                             r-rsample
                             r-rlang
                             r-purrr
                             r-parsnip
                             r-hardhat
                             r-h2o
                             r-glue
                             r-ggplot2
                             r-generics
                             r-dplyr
                             r-dials
                             r-cli))
    (native-inputs (list r-knitr))
    (home-page "https://agua.tidymodels.org/")
    (synopsis "'tidymodels' Integration with 'h2o'")
    (description
     "Create and evaluate models using tidymodels and h2o <https://h2o.ai/>.  The
package enables users to specify h2o as an engine for several modeling methods.")
    (license license:expat)))

(define-public r-agtboost
  (package
    (name "r-agtboost")
    (version "0.9.3")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "agtboost" version))
              (sha256
               (base32
                "1z2ys4cn859vas3q1if50k46cryn7wwy1pjqbc8n9dhdn5zxn3sk"))))
    (properties `((upstream-name . "agtboost")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcppeigen r-rcpp))
    (home-page "https://cran.r-project.org/package=agtboost")
    (synopsis "Adaptive and Automatic Gradient Boosting Computations")
    (description
     "Fast and automatic gradient tree boosting designed to avoid manual tuning and
cross-validation by utilizing an information theoretic approach.  This makes the
algorithm adaptive to the dataset at hand; it is completely automatic, and with
minimal worries of overfitting.  Consequently, the speed-ups relative to
state-of-the-art implementations can be in the thousands while mathematical and
technical knowledge required on the user are minimized.")
    (license license:gpl3)))

(define-public r-agsdest
  (package
    (name "r-agsdest")
    (version "2.3.4")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AGSDest" version))
              (sha256
               (base32
                "140bqzgaagdyzgxsn998jw2sxak448i47xyacn2psfnps440gfjr"))))
    (properties `((upstream-name . "AGSDest")))
    (build-system r-build-system)
    (propagated-inputs (list r-ldbounds))
    (home-page "https://cran.r-project.org/package=AGSDest")
    (synopsis "Estimation in Adaptive Group Sequential Trials")
    (description
     "Calculation of repeated confidence intervals as well as confidence intervals
based on the stage-wise ordering in group sequential designs and adaptive group
sequential designs.  For adaptive group sequential designs the confidence
intervals are based on the conditional rejection probability principle.
Currently the procedures do not support the use of futility boundaries or more
than one adaptive interim analysis.")
    (license license:gpl2+)))

(define-public r-agrotech
  (package
    (name "r-agrotech")
    (version "1.0.2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AgroTech" version))
              (sha256
               (base32
                "0pfw0sps9fbzzyy4d803j9fbg6a23nj18rks0bnrj9hms7a3vwfs"))))
    (properties `((upstream-name . "AgroTech")))
    (build-system r-build-system)
    (propagated-inputs (list r-xlsx
                             r-readxl
                             r-nortest
                             r-lmtest
                             r-gridextra
                             r-ggrepel
                             r-ggplot2
                             r-crayon))
    (home-page "https://cran.r-project.org/package=AgroTech")
    (synopsis "Data Analysis of Pesticide Application Technology")
    (description
     "In total it has 7 functions, three for calculating machine calibration, which
determine application rate (L/ha), nozzle flow (L/min) and amount of product (L
or kg) to be added.  to the tank with each sprayer filling.  Two functions for
graphs of the flow distribution of the nozzles (L/min) in the application bar
and, of the temporal variability of the meteorological conditions (air
temperature, relative humidity of the air and wind speed).  Two functions to
determine the spray deposit (uL/cm2), through the methodology called
spectrophotometry, with the aid of bright blue (Palladini, L.A., Raetano, C.G.,
Velini, E.D. (2005), <doi:10.1590/S0103-90162005000500005>) or metallic markers
(Chaim, A., Castro, V.L.S.S., Correles, F.M., Galvão, J.A.H., Cabral, O.M.R.,
Nicolella, G. (1999), <doi:10.1590/S0100-204X1999000500003>).  The package
supports the analysis and representation of information, using a single free
software that meets the most diverse areas of activity in application
technology.")
    (license license:gpl2+)))

(define-public r-agrostab
  (package
    (name "r-agrostab")
    (version "0.1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "agrostab" version))
              (sha256
               (base32
                "0mcskv3144j594wqljzn5pwbhkxh6sb76b1c2wabzjvi61zrapiv"))))
    (properties `((upstream-name . "agrostab")))
    (build-system r-build-system)
    (propagated-inputs (list r-rlang r-ggplot2 r-dplyr))
    (home-page "https://cran.r-project.org/package=agrostab")
    (synopsis "Stability Analysis for Agricultural Research")
    (description
     "Statistical procedures to perform stability analysis in plant breeding and to
identify stable genotypes under diverse environments.  It is possible to
calculate coefficient of homeostaticity by Khangildin et al. (1979), variance of
specific adaptive ability by Kilchevsky&Khotyleva (1989), weighted
homeostaticity index by Martynov (1990), steadiness of stability index by
Udachin (1990), superiority measure by Lin&Binn (1988) <doi:10.4141/cjps88-018>,
regression on environmental index by Erberhart&Rassel (1966)
<doi:10.2135/cropsci1966.0011183X000600010011x>, Tai's (1971) stability
parameters <doi:10.2135/cropsci1971.0011183X001100020006x>, stability variance
by Shukla (1972) <doi:10.1038/hdy.1972.87>, ecovalence by Wricke (1962),
nonparametric stability parameters by Nassar&Huehn (1987) <doi:10.2307/2531947>,
Francis&Kannenberg's parameters of stability (1978) <doi:10.4141/cjps78-157>.")
    (license license:gpl2)))

(define-public r-agroreg
  (package
    (name "r-agroreg")
    (version "1.2.7")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AgroReg" version))
              (sha256
               (base32
                "0kn7prhd9fzp2ibj12nz5cj5lag6bn7bmgva2xl7cf2b6pwmfijl"))))
    (properties `((upstream-name . "AgroReg")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcompanion
                             r-minpack-lm
                             r-ggplot2
                             r-egg
                             r-drc
                             r-dplyr
                             r-broom
                             r-boot))
    (home-page "https://agror.shinyapps.io/agroreg_shiny/")
    (synopsis "Regression Analysis Linear and Nonlinear for Agriculture")
    (description
     "Linear and nonlinear regression analysis common in agricultural science articles
(Archontoulis & Miguez (2015). <doi:10.2134/agronj2012.0506>).  The package
includes polynomial, exponential, gaussian, logistic, logarithmic, segmented,
non-parametric models, among others.  The functions return the model
coefficients and their respective p values, coefficient of determination, root
mean square error, AIC, BIC, as well as graphs with the equations automatically.")
    (license license:gpl2+)))

(define-public r-agror
  (package
    (name "r-agror")
    (version "1.3.2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AgroR" version))
              (sha256
               (base32
                "098ichvfsx7v1mawwy4mcxw7llfxkp7iqhnkawqq5f4lsjhr376h"))))
    (properties `((upstream-name . "AgroR")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcolorbrewer
                             r-nortest
                             r-multcompview
                             r-multcomp
                             r-mass
                             r-lmtest
                             r-lme4
                             r-knitr
                             r-gtools
                             r-gridextra
                             r-ggrepel
                             r-ggplot2
                             r-emmeans
                             r-dunn-test
                             r-drc
                             r-crayon
                             r-cowplot))
    (home-page "https://agronomiar.github.io/AgroR_package/index.html")
    (synopsis "Experimental Statistics and Graphics for Agricultural Sciences")
    (description
     "This package performs the analysis of completely randomized experimental designs
(CRD), randomized blocks (RBD) and Latin square (LSD), experiments in double and
triple factorial scheme (in CRD and RBD), experiments in subdivided plot scheme
(in CRD and RBD), subdivided and joint analysis of experiments in CRD and RBD,
linear regression analysis, test for two samples.  The package performs analysis
of variance, ANOVA assumptions and multiple comparison test of means or
regression, according to Pimentel-Gomes (2009, ISBN: 978-85-7133-055-9),
nonparametric test (Conover, 1999, ISBN: 0471160687), test for two samples,
joint analysis of experiments according to Ferreira (2018, ISBN:
978-85-7269-566-4) and generalized linear model (glm) for binomial and Poisson
family in CRD and RBD (Carvalho, FJ (2019), <doi:10.14393/ufu.te.2019.1244>).
It can also be used to obtain descriptive measures and graphics, in addition to
correlations and creative graphics used in agricultural sciences (Agronomy,
Zootechnics, Food Science and related areas).")
    (license license:gpl2+)))

(define-public r-agroclim
  (package
    (name "r-agroclim")
    (version "0.3.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "agroclim" version))
              (sha256
               (base32
                "06mv18a73dpcdw2y2df83rx9kfxsd5x2zv6j5md3yzm9ij3rylvx"))))
    (properties `((upstream-name . "agroclim")))
    (build-system r-build-system)
    (propagated-inputs (list r-zoo
                             r-sp
                             r-reshape
                             r-raster
                             r-ncdf4
                             r-multiapply
                             r-gtable
                             r-ggpubr
                             r-ggplot2
                             r-ggforce
                             r-easyncdf
                             r-cowplot
                             r-abind))
    (home-page "https://cran.r-project.org/package=agroclim")
    (synopsis "Climatic Indices for Agriculture")
    (description
     "Collection of functions to compute agroclimatic indices useful to zoning areas
based on climatic variables and to evaluate the importance of temperature and
precipitation for individual crops, or in general for agricultural lands.")
    (license license:gpl2+)))

(define-public r-agrmt
  (package
    (name "r-agrmt")
    (version "1.42.8")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "agrmt" version))
              (sha256
               (base32
                "1czxcyqrmcpjh4h77p9c6gb63aj0mi1b8cdxp3q6r0k7dy8db7ad"))))
    (properties `((upstream-name . "agrmt")))
    (build-system r-build-system)
    (home-page "http://agrmt.r-forge.r-project.org")
    (synopsis
     "Calculate Concentration and Dispersion in Ordered Rating Scales")
    (description
     "Calculates concentration and dispersion in ordered rating scales.  It implements
various measures of concentration and dispersion to describe what researchers
variably call agreement, concentration, consensus, dispersion, or polarization
among respondents in ordered data.  It also implements other related measures to
classify distributions.  In addition to a generic city-block based concentration
measure and a generic dispersion measure, the package implements various
measures, including van der Eijk's (2001) <DOI: 10.1023/A:1010374114305> measure
of agreement A, measures of concentration by Leik, Tatsle and Wierman, Blair and
Lacy, Kvalseth, Berry and Mielke, Reardon, and Garcia-Montalvo and
Reynal-Querol.  Furthermore, the package provides an implementation of Galtungs
AJUS-system to classify distributions, as well as a function to identify the
position of multiple modes.")
    (license license:expat)))

(define-public r-agriwater
  (package
    (name "r-agriwater")
    (version "1.0.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "agriwater" version))
              (sha256
               (base32
                "1mssd0nxj8ayc3b2qcc7qzx93cnwnlxrnhn3rdknxc8iixkf40l8"))))
    (properties `((upstream-name . "agriwater")))
    (build-system r-build-system)
    (propagated-inputs (list r-sp r-rgdal r-raster))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=agriwater")
    (synopsis "Evapotranspiration and Energy Fluxes Spatial Analysis")
    (description
     "Spatial modeling of energy balance and actual evapotranspiration using satellite
images and meteorological data.  Options of satellite are: Landsat-8 (with and
without thermal bands), Sentinel-2 and MODIS. Respectively spatial resolutions
are 30, 100, 10 and 250 meters.  User can use data from a single meteorological
station or a grid of meteorological stations (using any spatial interpolation
method).  Silva, Teixeira, and Manzione (2019)
<doi:10.1016/j.envsoft.2019.104497>.")
    (license license:expat)))

(define-public r-agritutorial
  (package
    (name "r-agritutorial")
    (version "0.1.5")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "agriTutorial" version))
              (sha256
               (base32
                "0c0p0bqcrnx34q5brnvgq10wkzahvgyybaz2xfmcghbdvzahd2dx"))))
    (properties `((upstream-name . "agriTutorial")))
    (build-system r-build-system)
    (propagated-inputs (list r-pbkrtest
                             r-nlme
                             r-lmertest
                             r-lattice
                             r-ggplot2
                             r-emmeans))
    (home-page "https://cran.r-project.org/package=agriTutorial")
    (synopsis "Tutorial Analysis of Some Agricultural Experiments")
    (description
     "Example software for the analysis of data from designed experiments, especially
agricultural crop experiments.  The basics of the analysis of designed
experiments are discussed using real examples from agricultural field trials.  A
range of statistical methods using a range of R statistical packages are
exemplified .  The experimental data is made available as separate data sets for
each example and the R analysis code is made available as example code.  The
example code can be readily extended, as required.")
    (license license:gpl2+)))

(define-public r-agrifeature
  (package
    (name "r-agrifeature")
    (version "1.0.3")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "agrifeature" version))
              (sha256
               (base32
                "0zbjmgwajwihgvs1c3swddx09m6954sihnpjdrqlgl5jhh7q2bgs"))))
    (properties `((upstream-name . "agrifeature")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=agrifeature")
    (synopsis "Agriculture Image Feature")
    (description
     "This package provides functions to calculate Gray Level Co-occurrence
Matrix(GLCM), RGB-based Vegetative Index(RGB VI) and Normalized Difference
Vegetation Index(NDVI) family image features.  GLCM calculations are based on
Haralick (1973) <doi:10.1109/TSMC.1973.4309314>.")
    (license license:gpl3)))

(define-public r-agridat
  (package
    (name "r-agridat")
    (version "1.21")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "agridat" version))
              (sha256
               (base32
                "1ihsv56j5nn01mqff8sj2m0cd2s3qynyy1nz742fln8krxq916i9"))))
    (properties `((upstream-name . "agridat")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://kwstat.github.io/agridat/")
    (synopsis "Agricultural Datasets")
    (description
     "Datasets from books, papers, and websites related to agriculture.  Example
graphics and analyses are included.  Data come from small-plot trials,
multi-environment trials, uniformity trials, yield monitors, and more.")
    (license license:cc-by-sa4.0)))

(define-public r-agricolaeplotr
  (package
    (name "r-agricolaeplotr")
    (version "0.2.2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "agricolaeplotr" version))
              (sha256
               (base32
                "1xrsn9afdqzczaqam0aygm19vpgbq9aqh5b5qr9awj747sihpxjp"))))
    (properties `((upstream-name . "agricolaeplotr")))
    (build-system r-build-system)
    (propagated-inputs (list r-rmarkdown r-ggplot2 r-agricolae))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/jensharbers/agricolaeplotr")
    (synopsis
     "Visualization of Design of Experiments from the 'agricolae' Package")
    (description
     "Visualization of Design of Experiments from the agricolae package with ggplot2
framework The user provides an experiment design from the agricolae package,
calls the corresponding function and will receive a visualization with ggplot2
based functions that are specific for each design.  As there are many different
designs, each design is tested on its type.  The output can be modified with
standard ggplot2 commands or with other packages with ggplot2 function
extensions.")
    (license license:gpl3+)))

(define-public r-agricolae
  (package
    (name "r-agricolae")
    (version "1.3-5")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "agricolae" version))
              (sha256
               (base32
                "0pgcpp3g7j9cnxajm98ppsqz5dx33v7xnrq0gp50flwbc0sjb0l3"))))
    (properties `((upstream-name . "agricolae")))
    (build-system r-build-system)
    (propagated-inputs (list r-nlme r-mass r-klar r-cluster r-algdesign))
    (home-page "https://cran.r-project.org/package=agricolae")
    (synopsis "Statistical Procedures for Agricultural Research")
    (description
     "Original idea was presented in the thesis \"A statistical analysis tool for
agricultural research\" to obtain the degree of Master on science, National
Engineering University (UNI), Lima-Peru.  Some experimental data for the
examples come from the CIP and others research.  Agricolae offers extensive
functionality on experimental design especially for agricultural and plant
breeding experiments, which can also be useful for other purposes.  It supports
planning of lattice, Alpha, Cyclic, Complete Block, Latin Square, Graeco-Latin
Squares, augmented block, factorial, split and strip plot designs.  There are
also various analysis facilities for experimental data, e.g. treatment
comparison procedures and several non-parametric tests comparison, biodiversity
indexes and consensus cluster.")
    (license (list license:gpl2+ license:gpl3+))))

(define-public r-agreementinterval
  (package
    (name "r-agreementinterval")
    (version "0.1.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AgreementInterval" version))
              (sha256
               (base32
                "1bvinzylvsaipa8mq15f45b6h37znavlrdl0rbrx1pqw52r7z8kv"))))
    (properties `((upstream-name . "AgreementInterval")))
    (build-system r-build-system)
    (propagated-inputs (list r-psych))
    (home-page "https://cran.r-project.org/package=AgreementInterval")
    (synopsis "Agreement Interval of Two Measurement Methods")
    (description
     "This package provides a tool for calculating agreement interval of two
measurement methods (Jason Liao (2015) <DOI:10.1515/ijb-2014-0030>) and present
results in plots with discordance rate and/or clinically meaningful limit to
quantify agreement quality.")
    (license license:expat)))

(define-public r-agree
  (package
    (name "r-agree")
    (version "0.5-3")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "agRee" version))
              (sha256
               (base32
                "1wi8jn14kpsj5z49my6fz8j6zxysddxm8svw86cnzsmnbj6mzq7x"))))
    (properties `((upstream-name . "agRee")))
    (build-system r-build-system)
    (propagated-inputs (list r-r2jags r-miscf r-lme4 r-coda))
    (home-page "https://cran.r-project.org/package=agRee")
    (synopsis "Various Methods for Measuring Agreement")
    (description
     "Bland-Altman plot and scatter plot with identity line for visualization and
point and interval estimates for different metrics related to
reproducibility/repeatability/agreement including the concordance correlation
coefficient, intraclass correlation coefficient, within-subject coefficient of
variation, smallest detectable difference, and mean normalized smallest
detectable difference.")
    (license (list license:gpl2+ license:gpl3+))))

(define-public r-agpris
  (package
    (name "r-agpris")
    (version "1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AGPRIS" version))
              (sha256
               (base32
                "0xlaz75d19adfq79sh5aa52bzpmjqawshay2a3vw9mq8l23z64if"))))
    (properties `((upstream-name . "AGPRIS")))
    (build-system r-build-system)
    (propagated-inputs (list r-spdep
                             r-spacetime
                             r-sp
                             r-rgdal
                             r-plyr
                             r-maxlik
                             r-matrixcalc
                             r-matrix))
    (home-page "https://cran.r-project.org/package=AGPRIS")
    (synopsis "AGricultural PRoductivity in Space")
    (description
     "Functionalities to simulate space-time data and to estimate dynamic-spatial
panel data models.  Estimators implemented are the BCML (Elhorst (2010),
<doi:10.1016/j.regsciurbeco.2010.03.003>), the MML (Elhorst (2010)
<doi:10.1016/j.regsciurbeco.2010.03.003>) and the INLA Bayesian estimator
(Lindgren and Rue, (2015) <doi:10.18637/jss.v063.i19>; Bivand, Gomez-Rubio and
Rue, (2015) <doi:10.18637/jss.v063.i20>) adapted to panel data.  The package
contains functions to replicate the analyses of the scientific article entitled
\"Agricultural Productivity in Space\" (Baldoni and Esposti (under revision)).")
    (license license:gpl3)))

(define-public r-agop
  (package
    (name "r-agop")
    (version "0.2-3")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "agop" version))
              (sha256
               (base32
                "1z90a07wzn5z4cbafwpfh3l3v1bgq9g89qbdjm51f78zynnb27dk"))))
    (properties `((upstream-name . "agop")))
    (build-system r-build-system)
    (home-page "http://www.gagolewski.com/software/")
    (synopsis "Aggregation Operators and Preordered Sets")
    (description
     "Tools supporting multi-criteria and group decision making, including variable
number of criteria, by means of aggregation operators, spread measures, fuzzy
logic connectives, fusion functions, and preordered sets.  Possible applications
include, but are not limited to, quality management, scientometrics, software
engineering, etc.")
    (license license:lgpl3+)))

(define-public r-aglm
  (package
    (name "r-aglm")
    (version "0.4.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "aglm" version))
              (sha256
               (base32
                "0rcyrzfi3l1k53c9qs1gfrcflnhdnri9sq6py8s6fw4wcn55kf67"))))
    (properties `((upstream-name . "aglm")))
    (build-system r-build-system)
    (propagated-inputs (list r-mathjaxr r-glmnet r-assertthat))
    (home-page "https://github.com/kkondo1981/aglm")
    (synopsis "Accurate Generalized Linear Model")
    (description
     "This package provides functions to fit Accurate Generalized Linear Model (AGLM)
models, visualize them, and predict for new data.  AGLM is defined as a
regularized GLM which applies a sort of feature transformations using a
discretization of numerical features and specific coding methodologies of dummy
variables.  For more information on AGLM, see Suguru Fujita, Toyoto Tanaka,
Kenji Kondo and Hirokazu Iwasawa (2020)
<https://www.institutdesactuaires.com/global/gene/link.php?doc_id=16273&fg=1>.")
    (license license:gpl2)))

(define-public r-aghq
  (package
    (name "r-aghq")
    (version "0.4.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "aghq" version))
              (sha256
               (base32
                "12zzadx0qfh5wg8092w777c9ymd1m6gq3gwmfp9pf9bn3s31vij3"))))
    (properties `((upstream-name . "aghq")))
    (build-system r-build-system)
    (propagated-inputs (list r-rlang r-polynom r-numderiv r-mvquad r-matrix))
    (home-page "https://cran.r-project.org/package=aghq")
    (synopsis "Adaptive Gauss Hermite Quadrature for Bayesian Inference")
    (description
     "Adaptive Gauss Hermite Quadrature for Bayesian inference.  The AGHQ method for
normalizing posterior distributions and making Bayesian inferences based on
them.  Functions are provided for doing quadrature and marginal Laplace
approximations, and summary methods are provided for making inferences based on
the results.  See Stringer (2021). \"Implementing Adaptive Quadrature for
Bayesian Inference: the aghq Package\" <arXiv:2101.04468>.")
    (license license:gpl3+)))

(define-public r-aghmatrix
  (package
    (name "r-aghmatrix")
    (version "2.0.4")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AGHmatrix" version))
              (sha256
               (base32
                "1pvnv3fzxfdzjz9il0022k46kkcb57ypz31qn0br7mck64bkzsia"))))
    (properties `((upstream-name . "AGHmatrix")))
    (build-system r-build-system)
    (propagated-inputs (list r-zoo r-matrix))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/rramadeu/AGHmatrix")
    (synopsis "Relationship Matrices for Diploid and Autopolyploid Species")
    (description
     "Computation of A (pedigree), G (genomic-base), and H (A corrected by G)
relationship matrices for diploid and autopolyploid species.  Several methods
are implemented considering additive and non-additive models.")
    (license license:gpl3)))

(define-public r-aggregater
  (package
    (name "r-aggregater")
    (version "0.1.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AggregateR" version))
              (sha256
               (base32
                "1s2q888bqx6ilisv5s4g8ryja97nz6cz4ycm4sw1i63l5wjrwljc"))))
    (properties `((upstream-name . "AggregateR")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble r-ncmisc r-data-table))
    (home-page "https://cran.r-project.org/package=AggregateR")
    (synopsis "Aggregate Numeric, Date and Categorical Variables")
    (description
     "Convenience functions for aggregating a data frame or data table.  Currently
mean, sum and variance are supported.  For Date variables, the recency and
duration are supported.  There is also support for dummy variables in predictive
contexts.  Code has been completely re-written in data.table for computational
speed.")
    (license license:gpl2+)))

(define-public r-ageg
  (package
    (name "r-ageg")
    (version "1.0.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ageg" version))
              (sha256
               (base32
                "0dcmwgznxf1jjsifpm3nn3jk25mm27l6f6f6jfi2n3crxgqfizyv"))))
    (properties `((upstream-name . "ageg")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=ageg")
    (synopsis "Age Grouping Functions")
    (description
     "Pair of simple convenience functions to convert a vector of birth dates to age
and age distributions.  These functions may be helpful when related age and
custom age distributions are desired given a vector of birth dates.")
    (license license:expat)))

(define-public r-agd
  (package
    (name "r-agd")
    (version "0.39")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AGD" version))
              (sha256
               (base32
                "0hmq684snnffc2v7vmns4ky200a6zh1ggiap03n5cvpb3nlqc6lr"))))
    (properties `((upstream-name . "AGD")))
    (build-system r-build-system)
    (propagated-inputs (list r-gamlss-dist r-gamlss))
    (home-page "https://github.com/stefvanbuuren/AGD")
    (synopsis "Analysis of Growth Data")
    (description
     "Tools for the analysis of growth data: to extract an LMS table from a gamlss
object, to calculate the standard deviation scores and its inverse, and to
superpose two wormplots from different models.  The package contains a some
varieties of reference tables, especially for The Netherlands.")
    (license (list license:gpl2 license:gpl3))))

(define-public r-ag5tools
  (package
    (name "r-ag5tools")
    (version "0.0.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ag5Tools" version))
              (sha256
               (base32
                "1390acslndzvvhdc6pk9cfvhval1wqgiic353f03qv0rvhxbyzad"))))
    (properties `((upstream-name . "ag5Tools")))
    (build-system r-build-system)
    (propagated-inputs (list r-terra r-reticulate r-fs))
    (native-inputs (list r-knitr))
    (home-page "https://agrdatasci.github.io/ag5Tools/")
    (synopsis "Toolbox for Downloading and Extracting Copernicus AgERA5 Data")
    (description
     "Tools for downloading and extracting data from the Copernicus
\"Agrometeorological indicators from 1979 to present derived from reanalysis\"
<https://cds.climate.copernicus.eu/cdsapp#!/dataset/sis-agrometeorological-indicators?tab=overview>
(AgERA5).")
    (license license:expat)))

(define-public r-afttest
  (package
    (name "r-afttest")
    (version "4.2.1.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "afttest" version))
              (sha256
               (base32
                "06l11gjfv2a4jsdi7f88w7pk04a2mfl2jx969z7w4n4nlmz0bz8z"))))
    (properties `((upstream-name . "afttest")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival
                             r-rcpparmadillo
                             r-rcpp
                             r-gridextra
                             r-ggplot2
                             r-aftgee))
    (home-page "https://github.com/WooJungBae/afttest")
    (synopsis "Model Diagnostics for Accelerated Failure Time Models")
    (description
     "This package provides a collection of model checking methods for semiparametric
accelerated failure time (AFT) models under the rank-based approach.  For the
(computational) efficiency, Gehan's weight is used.  It provides functions to
verify whether the observed data fit the specific model assumptions such as a
functional form of each covariate, a link function, and an omnibus test.  The
p-value offered in this package is based on the Kolmogorov-type supremum test
and the variance of the proposed test statistics is estimated through the
re-sampling method.  Furthermore, a graphical technique to compare the shape of
the observed residual to a number of the approximated realizations is provided.")
    (license license:gpl3+)))

(define-public r-afthd
  (package
    (name "r-afthd")
    (version "1.1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "afthd" version))
              (sha256
               (base32
                "0gg2cp3sj28f3pi5rqh737hna3imwarwas01jacm0m2h27587k7y"))))
    (properties `((upstream-name . "afthd")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival r-rstpm2 r-r2jags r-photobiology
                             r-glmnet))
    (home-page "https://cran.r-project.org/package=afthd")
    (synopsis "Accelerated Failure Time for High Dimensional Data with MCMC")
    (description
     "This package provides functions for Posterior estimates of Accelerated Failure
Time(AFT) model with MCMC and Maximum likelihood estimates of AFT model without
MCMC for univariate and multivariate analysis in high dimensional gene
expression data are available in this afthd package.  AFT model with Bayesian
framework for multivariate in high dimensional data has been proposed by
Prabhash et al.(2016) <doi:10.21307/stattrans-2016-046>.")
    (license license:gpl3)))

(define-public r-aftgee
  (package
    (name "r-aftgee")
    (version "1.1.6")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "aftgee" version))
              (sha256
               (base32
                "1sq6d6zkr4whg61phz22gb5zh7wxg2il39w2g5s812i4hiipqj4r"))))
    (properties `((upstream-name . "aftgee")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival r-mass r-geepack r-bb))
    (home-page "https://github.com/stc04003/aftgee")
    (synopsis
     "Accelerated Failure Time Model with Generalized Estimating Equations")
    (description
     "This package provides a collection of methods for both the rank-based estimates
and least-square estimates to the Accelerated Failure Time (AFT) model.  For
rank-based estimation, it provides approaches that include the computationally
efficient Gehan's weight and the general's weight such as the logrank weight.
Details of the rank-based estimation can be found in Chiou et al. (2014)
<doi:10.1007/s11222-013-9388-2> and Chiou et al. (2015) <doi:10.1002/sim.6415>.
For the least-square estimation, the estimating equation is solved with
generalized estimating equations (GEE).  Moreover, in multivariate cases, the
dependence working correlation structure can be specified in GEE's setting.
Details on the least-squares estimation can be found in Chiou et al. (2014)
<doi:10.1007/s10985-014-9292-x>.")
    (license license:gpl3+)))

(define-public r-africamonitor
  (package
    (name "r-africamonitor")
    (version "0.2.2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "africamonitor" version))
              (sha256
               (base32
                "06k600wbvzxy3lk7niil84xndcnbar88z07qxyqwklvl07jcpc9h"))))
    (properties `((upstream-name . "africamonitor")))
    (build-system r-build-system)
    (propagated-inputs (list r-rmysql r-dbi r-data-table r-collapse))
    (home-page "https://africamonitor.ifw-kiel.de/")
    (synopsis "Africa Macroeconomic Monitor Database API")
    (description
     "An R API providing access to a relational database with macroeconomic data for
Africa.  The database contains >700 macroeconomic time series from mostly
international sources, grouped into 50 macroeconomic and development-related
topics.  Series are carefully selected on the basis of data coverage for Africa,
frequency, and relevance to the macro-development context.  The project is part
of the Kiel Institute Africa Initiative
<https://www.ifw-kiel.de/institute/initiatives/kielinstituteafricainitiative/>,
which, amongst other things, aims to develop a parsimonious database with highly
relevant indicators to monitor macroeconomic developments in Africa, accessible
through a fast API and a web-based platform at
<https://africamonitor.ifw-kiel.de/>.  The database is maintained at the Kiel
Institute for the World Economy <https://www.ifw-kiel.de/>.")
    (license license:gpl3)))

(define-public r-afr
  (package
    (name "r-afr")
    (version "0.2.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AFR" version))
              (sha256
               (base32
                "1in4wd491y37iwac8k0b4wj0gpvz01r65qg2hc8m6v4mb0572clf"))))
    (properties `((upstream-name . "AFR")))
    (build-system r-build-system)
    (propagated-inputs (list r-zoo
                             r-xts
                             r-writexl
                             r-tseries
                             r-rlang
                             r-regclass
                             r-olsrr
                             r-nortest
                             r-nlme
                             r-mfilter
                             r-lmtest
                             r-gridextra
                             r-goftest
                             r-ggplot2
                             r-forecast
                             r-cli
                             r-car))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=AFR")
    (synopsis
     "Toolkit for Regression Analysis of Kazakhstan Banking Sector Data")
    (description
     "Tool is created for regression, prediction and forecast analysis of
macroeconomic and credit data.  The package includes functions from existing R
packages adapted for banking sector of Kazakhstan.  The purpose of the package
is to optimize statistical functions for easier interpretation for bank analysts
and non-statisticians.")
    (license license:gpl2)))

(define-public r-afmtoolkit
  (package
    (name "r-afmtoolkit")
    (version "0.0.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "afmToolkit" version))
              (sha256
               (base32
                "1pm3xyh9vq10mmfgknlvlfr9f027xprrgy1dvbbxpi7f111hv1gl"))))
    (properties `((upstream-name . "afmToolkit")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble
                             r-scales
                             r-minpack-lm
                             r-gridextra
                             r-ggplot2
                             r-dplyr
                             r-dbi
                             r-assertthat))
    (home-page "https://cran.r-project.org/package=afmToolkit")
    (synopsis
     "Functions for Atomic Force Microscope Force-Distance Curves Analysis")
    (description
     "Set of functions for analyzing Atomic Force Microscope (AFM) force-distance
curves.  It allows to obtain the contact and unbinding points, perform the
baseline correction, estimate the Young's modulus, fit up to two exponential
decay function to a stress-relaxation / creep experiment, obtain adhesion
energies.  These operations can be done either over a single F-d curve or over a
set of F-d curves in batch mode.")
    (license (list license:gpl2+ license:gpl3+))))

(define-public r-afm
  (package
    (name "r-afm")
    (version "2.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AFM" version))
              (sha256
               (base32
                "1l0yd68h8vlii1437zhyrxj6fq1ghfaqclk860c25q2d055ajnqd"))))
    (properties `((upstream-name . "AFM")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr
                             r-sp
                             r-shinyjs
                             r-shiny
                             r-scales
                             r-rgl
                             r-pracma
                             r-png
                             r-plyr
                             r-moments
                             r-mixtools
                             r-igraph
                             r-gstat
                             r-gridextra
                             r-ggplot2
                             r-fractaldim
                             r-fftwtools
                             r-dbscan
                             r-data-table))
    (home-page "https://cran.r-project.org/package=AFM")
    (synopsis "Atomic Force Microscope Image Analysis")
    (description
     "This package provides Atomic Force Microscope images analysis such as Gaussian
mixes identification, Power Spectral Density, roughness against lengthscale,
experimental variogram and variogram models, fractal dimension and scale, 2D
network analysis.  The AFM images can be exported to STL format for 3D printing.")
    (license license:agpl3)))

(define-public r-afheritability
  (package
    (name "r-afheritability")
    (version "0.1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AFheritability" version))
              (sha256
               (base32
                "03w0a4z2x539ykyzdxm1mfqkhzz03cg0aqvgi062jrrm5m6f57ix"))))
    (properties `((upstream-name . "AFheritability")))
    (build-system r-build-system)
    (propagated-inputs (list r-shiny r-reshape2 r-mvtnorm r-ggplot2))
    (home-page "https://cran.r-project.org/package=AFheritability")
    (synopsis
     "The Attributable Fraction (AF) Described as a Function of Disease Heritability, Prevalence and Intervention Specific Factors")
    (description
     "The AFfunction() is a function which returns an estimate of the Attributable
Fraction (AF) and a plot of the AF as a function of heritability, disease
prevalence, size of target group and intervention effect.  Since the AF is a
function of several factors, a shiny app is used to better illustrate how the
relationship between the AF and heritability depends on several other factors.
The app is ran by the function runShinyApp().  For more information see
Dahlqwist E et al. (2019) <doi:10.1007/s00439-019-02006-8>.")
    (license (list license:gpl2 license:gpl3))))

(define-public r-affluenceindex
  (package
    (name "r-affluenceindex")
    (version "2.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "affluenceIndex" version))
              (sha256
               (base32
                "0vcg4gphs0yxdxsgw7kj9r3hvjpfs2z8sjvllvfw9ki3y7jy5jb8"))))
    (properties `((upstream-name . "affluenceIndex")))
    (build-system r-build-system)
    (propagated-inputs (list r-spatstat-geom r-spatstat))
    (home-page "https://cran.r-project.org/package=affluenceIndex")
    (synopsis "Affluence (Richness) Indices")
    (description
     "Enables to compute the statistical indices of affluence (richness) with
bootstrap errors, and inequality and polarization indices.  Moreover, gives the
possibility of calculation of Medeiros affluence line.  In 2.1 version some
simple errors are fixed.")
    (license license:gpl2)))

(define-public r-affinitymatrix
  (package
    (name "r-affinitymatrix")
    (version "0.1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "affinitymatrix" version))
              (sha256
               (base32
                "10i7wzl4xiphj5f466ga7c4ha3mkyqn63x1z0jyx50m0b84sggq1"))))
    (properties `((upstream-name . "affinitymatrix")))
    (build-system r-build-system)
    (propagated-inputs (list r-mass r-hmisc r-ggrepel r-ggplot2 r-expm))
    (home-page "https://cran.r-project.org/package=affinitymatrix")
    (synopsis "Estimation of Affinity Matrix")
    (description
     "Tools to study sorting patterns in matching markets and to estimate the affinity
matrix of both the bipartite one-to-one matching model without frictions and
with Transferable Utility by Dupuy and Galichon (2014) <doi:10.1086/677191> and
its unipartite variant by Ciscato', Galichon and Gousse (2020)
<doi:10.1086/704611>.  It also contains all the necessary tools to implement the
saliency analysis, to run rank tests of the affinity matrix and to build tables
and plots summarizing the findings.")
    (license license:gpl3)))

(define-public r-affinity
  (package
    (name "r-affinity")
    (version "0.2.5")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "affinity" version))
              (sha256
               (base32
                "0nfh3g8nifv5773pihgzxh62wa837i2dk1kgf15z28cb5xfj2y8h"))))
    (properties `((upstream-name . "affinity")))
    (build-system r-build-system)
    (propagated-inputs (list r-reproj r-raster))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/hypertidy/affinity")
    (synopsis
     "Raster Georeferencing, Grid Affine Transforms, Cell Abstraction")
    (description
     "Tools for raster georeferencing, grid affine transforms, and general raster
logic.  These functions provide converters between raster specifications, world
vector, geotransform, RasterIO window, and RasterIO window in sf package list
format.  There are functions to offset a matrix by padding any of four corners
(useful for vectorizing neighbourhood operations), and helper functions to
harvesting user clicks on a graphics device to use for simple georeferencing of
images.  Methods used are available from
<https://en.wikipedia.org/wiki/World_file> and
<https://gdal.org/user/raster_data_model.html>.")
    (license license:gpl3)))

(define-public r-afdx
  (package
    (name "r-afdx")
    (version "1.1.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "afdx" version))
              (sha256
               (base32
                "1654vxakdd11b5zhwy1vcv127xk5rifan6fs1k6w1qsk74j4drqv"))))
    (properties `((upstream-name . "afdx")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr r-maxlik r-magrittr r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/johnaponte/afdx")
    (synopsis "Diagnosis Performance Using Attributable Fraction")
    (description
     "Estimate diagnosis performance (Sensitivity, Specificity, Positive predictive
value, Negative predicted value) of a diagnostic test where can not measure the
golden standard but can estimate it using the attributable fraction.")
    (license license:gpl3+)))

(define-public r-afc
  (package
    (name "r-afc")
    (version "1.4.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "afc" version))
              (sha256
               (base32
                "1iy1wa88kf6zi6x7lbd0jdir653cvzvdraliqpxbac413wwb5gwl"))))
    (properties `((upstream-name . "afc")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=afc")
    (synopsis "Generalized Discrimination Score")
    (description
     "This is an implementation of the Generalized Discrimination Score (also known as
Two Alternatives Forced Choice Score, 2AFC) for various representations of
forecasts and verifying observations.  The Generalized Discrimination Score is a
generic forecast verification framework which can be applied to any of the
following verification contexts: dichotomous, polychotomous (ordinal and
nominal), continuous, probabilistic, and ensemble.  A comprehensive description
of the Generalized Discrimination Score, including all equations used in this
package, is provided by Mason and Weigel (2009) <doi:10.1175/MWR-D-10-05069.1>.")
    (license license:gpl3)))

(define-public r-af
  (package
    (name "r-af")
    (version "0.1.5")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AF" version))
              (sha256
               (base32
                "1r87ra55g0qm2s8cgsmdwck93ia2vr8zfab3in45mxm5xc501xgk"))))
    (properties `((upstream-name . "AF")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival r-stdreg r-ivtools r-drgee
                             r-data-table))
    (home-page "https://cran.r-project.org/package=AF")
    (synopsis
     "Model-Based Estimation of Confounder-Adjusted Attributable Fractions")
    (description
     "Estimates the attributable fraction in different sampling designs adjusted for
measured confounders using logistic regression (cross-sectional and case-control
designs), conditional logistic regression (matched case-control design), Cox
proportional hazard regression (cohort design with time-to- event outcome),
gamma-frailty model with a Weibull baseline hazard and instrumental variables
analysis.  An exploration of the AF with a genetic exposure can be found in the
package AFheritability Dahlqwist E et al. (2019)
<doi:10.1007/s00439-019-02006-8>.")
    (license (list license:gpl2 license:gpl3))))

(define-public r-aerosampler
  (package
    (name "r-aerosampler")
    (version "0.1.14")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AeroSampleR" version))
              (sha256
               (base32
                "027lf82kpllz8v0g2mbbjx1yc2nmw5i0pfhmnhay3ms0yc4p4sbm"))))
    (properties `((upstream-name . "AeroSampleR")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyselect
                             r-tidyr
                             r-stringr
                             r-purrr
                             r-ggthemes
                             r-ggplot2
                             r-flextable
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=AeroSampleR")
    (synopsis "Estimate Aerosol Particle Collection Through Sample Lines")
    (description
     "Estimate ideal efficiencies of aerosol sampling through sample lines.  Functions
were developed consistent with the approach described in Hogue, Mark; Thompson,
Martha; Farfan, Eduardo; Hadlock, Dennis, (2014), \"Hand Calculations for
Transport of Radioactive Aerosols through Sampling Systems\" Health Phys 106, 5,
S78-S87, <doi:10.1097/HP.0000000000000092>.")
    (license license:gpl3)))

(define-public r-aerobiology
  (package
    (name "r-aerobiology")
    (version "2.0.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AeRobiology" version))
              (sha256
               (base32
                "14d5gjx53v2wfij8m4br0k7lfi6x2frc8ny1li4g8c05qv2dvnbb"))))
    (properties `((upstream-name . "AeRobiology")))
    (build-system r-build-system)
    (propagated-inputs (list r-zoo
                             r-writexl
                             r-tidyr
                             r-scales
                             r-plotly
                             r-lubridate
                             r-ggvis
                             r-ggplot2
                             r-dplyr
                             r-data-table
                             r-circular))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=AeRobiology")
    (synopsis "Computational Tool for Aerobiological Data")
    (description
     "Different tools for managing databases of airborne particles, elaborating the
main calculations and visualization of results.  In a first step, data are
checked using tools for quality control and all missing gaps are completed.
Then, the main parameters of the pollen season are calculated and represented
graphically.  Multiple graphical tools are available: pollen calendars,
phenological plots, time series, tendencies, interactive plots, abundance
plots...")
    (license license:gpl3)))

(define-public r-aep
  (package
    (name "r-aep")
    (version "0.1.4")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AEP" version))
              (sha256
               (base32
                "15b48vbl36b6wmjszm28p0mawg5kwsjglbrb8cndf3zsvx95zdq1"))))
    (properties `((upstream-name . "AEP")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=AEP")
    (synopsis
     "Statistical Modelling for Asymmetric Exponential Power Distribution")
    (description
     "Developed for Computing the probability density function, cumulative
distribution function, random generation, estimating the parameters of
asymmetric exponential power distribution, and robust regression analysis with
error term that follows asymmetric exponential power distribution.  The
asymmetric exponential power distribution studied here is a special case of that
introduced by Dongming and Zinde-Walsh (2009)
<doi:10.1016/j.jeconom.2008.09.038>.")
    (license license:gpl2+)))

(define-public r-aeenrich
  (package
    (name "r-aeenrich")
    (version "1.1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AEenrich" version))
              (sha256
               (base32
                "049z696mkwha90w84l60r11q12r3jlam6kyh8abiy0zk2k425san"))))
    (properties `((upstream-name . "AEenrich")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-rlang
                             r-qvalue
                             r-modelr
                             r-magrittr
                             r-foreach
                             r-dplyr
                             r-doparallel))
    (home-page "https://github.com/umich-biostatistics/AEenrich")
    (synopsis "Adverse Event Enrichment Tests")
    (description
     "We extend existing gene enrichment tests to perform adverse event enrichment
analysis.  Unlike the continuous gene expression data, adverse event data are
counts.  Therefore, adverse event data has many zeros and ties.  We propose two
enrichment tests.  One is a modified Fisher's exact test based on pre-selected
significant adverse events, while the other is based on a modified
Kolmogorov-Smirnov statistic.  We add Covariate adjustment to improve the
analysis.\"Adverse event enrichment tests using VAERS\" Shuoran Li, Lili Zhao
(2020) <arXiv:2007.02266>.")
    (license license:gpl2)))

(define-public r-aedforecasting
  (package
    (name "r-aedforecasting")
    (version "0.20.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AEDForecasting" version))
              (sha256
               (base32
                "16q2sn5zzvysyy3r32jnr21pbdkkn0k0sbarni6fdkx7pj27yijn"))))
    (properties `((upstream-name . "AEDForecasting")))
    (build-system r-build-system)
    (propagated-inputs (list r-signal r-forecast r-changepoint))
    (home-page "https://cran.r-project.org/package=AEDForecasting")
    (synopsis "Change Point Analysis in ARIMA Forecasting")
    (description
     "Package to incorporate change point analysis in ARIMA forecasting.")
    (license license:gpl3)))

(define-public r-adwordsr
  (package
    (name "r-adwordsr")
    (version "0.3.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "adwordsR" version))
              (sha256
               (base32
                "1w5qg4psm8pj89f09pz7in8zkafaimik1n6hx29y55jpmbxbk2gn"))))
    (properties `((upstream-name . "adwordsR")))
    (build-system r-build-system)
    (propagated-inputs (list r-rjson r-rcurl))
    (home-page "https://www.branded3.com/")
    (synopsis "Access the 'Google Adwords' API")
    (description
     "Allows access to selected services that are part of the Google Adwords API
<https://developers.google.com/adwords/api/docs/guides/start>.  Google Adwords
is an online advertising service by Google', that delivers Ads to users.  This
package offers a authentication process using OAUTH2'.  Currently, there are two
methods of data of accessing the API, depending on the type of request.  One
method uses SOAP requests which require building an XML structure and then sent
to the API. These are used for the ManagedCustomerService and the
TargetingIdeaService'.  The second method is by building AWQL queries for the
reporting side of the Google Adwords API.")
    (license license:expat)))

(define-public r-adwave
  (package
    (name "r-adwave")
    (version "1.3")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "adwave" version))
              (sha256
               (base32
                "11iy50ng0zxvwsvdsvx262j8zgqaai308lp5is47az7xzvk57mx7"))))
    (properties `((upstream-name . "adwave")))
    (build-system r-build-system)
    (propagated-inputs (list r-waveslim))
    (home-page "https://doi.org/10.1534/genetics.115.176842")
    (synopsis "Wavelet Analysis of Genomic Data from Admixed Populations")
    (description
     "This package implements wavelet-based approaches for describing population
admixture.  Principal Components Analysis (PCA) is used to define the population
structure and produce a localized admixture signal for each individual.  Wavelet
summaries of the PCA output describe variation present in the data and can be
related to population-level demographic processes.  For more details, see J
Sanderson, H Sudoyo, TM Karafet, MF Hammer and MP Cox.  2015.  Reconstructing
past admixture processes from local genomic ancestry using wavelet
transformation.  Genetics 200:469-481 <doi:10.1534/genetics.115.176842>.")
    (license license:gpl2+)))

(define-public r-adw
  (package
    (name "r-adw")
    (version "0.2.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "adw" version))
              (sha256
               (base32
                "0yynzw4sxz42vqq4dxb0cs123mbir5nnsq45v9agjw889m7k7prj"))))
    (properties `((upstream-name . "adw")))
    (build-system r-build-system)
    (propagated-inputs (list r-terra r-geosphere))
    (home-page "https://github.com/PanfengZhang/adw")
    (synopsis "Angular Distance Weighting Interpolation")
    (description
     "The irregularly-spaced data are interpolated onto regular latitude-longitude
grids by weighting each station according to its distance and angle from the
center of a search radius.")
    (license license:gpl3)))

(define-public r-advice
  (package
    (name "r-advice")
    (version "1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ADVICE" version))
              (sha256
               (base32
                "1p8186715lzk4prxaw5v0np9z1zfj9zbp124jrch0yygvkxksy7r"))))
    (properties `((upstream-name . "ADVICE")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=ADVICE")
    (synopsis
     "Automatic Direct Variable Selection via Interrupted Coefficient Estimation")
    (description
     "Accurate point and interval estimation methods for multiple linear regression
coefficients, under classical normal and independent error assumptions, taking
into account variable selection.")
    (license (license:fsdg-compatible "Unlimited"))))

(define-public r-adventr
  (package
    (name "r-adventr")
    (version "0.1.8")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "adventr" version))
              (sha256
               (base32
                "0nja1a2xhaimz1fg2bb838x9a37sswjqjc68mp59gbdwkfpdii37"))))
    (properties `((upstream-name . "adventr")))
    (build-system r-build-system)
    (propagated-inputs (list r-wrs2
                             r-tidyr
                             r-sjstats
                             r-sandwich
                             r-robust
                             r-readr
                             r-nlme
                             r-lm-beta
                             r-learnr
                             r-hmisc
                             r-ggplot2
                             r-ggally
                             r-forcats
                             r-effsize
                             r-effects
                             r-dplyr
                             r-car
                             r-boot
                             r-bayesfactor))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=adventr")
    (synopsis
     "Interactive R Tutorials to Accompany Field (2016), \"An Adventure in Statistics\"")
    (description
     "Interactive R tutorials written using learnr for Field (2016), \"An Adventure in
Statistics\", <ISBN:9781446210451>.  Topics include general workflow in R and
Rstudio', the R environment and tidyverse', summarizing data, model fitting,
central tendency, visualising data using ggplot2', inferential statistics and
robust estimation, hypothesis testing, the general linear model, comparing
means, repeated measures designs, factorial designs, multilevel models, growth
models, and generalized linear models (logistic regression).")
    (license license:gpl3)))

(define-public r-advdif4
  (package
    (name "r-advdif4")
    (version "0.7.18")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AdvDif4" version))
              (sha256
               (base32
                "1xdbk7w55cb2fh0mqlyrkdpnglrs55kyvvp32anvf2nw3ssrfmy7"))))
    (properties `((upstream-name . "AdvDif4")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=AdvDif4")
    (synopsis "Solving 1D Advection Bi-Flux Diffusion Equation")
    (description
     "This software solves an Advection Bi-Flux Diffusive Problem using the Finite
Difference Method FDM. Vasconcellos, J.F.V., Marinho, G.M., Zanni, J.H., 2016,
Numerical analysis of an anomalous diffusion with a bimodal flux distribution.
<doi:10.1016/j.rimni.2016.05.001>.  Silva, L.G., Knupp, D.C., Bevilacqua, L.,
Galeao, A.C.N.R., Silva Neto, A.J., 2014, Formulation and solution of an Inverse
Anomalous Diffusion Problem with Stochastic Techniques.
<doi:10.5902/2179460X13184>.  In this version, it is possible to include a
source as a function depending on space and time, that is, s(x,t).")
    (license license:gpl3)))

(define-public r-advbinomapps
  (package
    (name "r-advbinomapps")
    (version "1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AdvBinomApps" version))
              (sha256
               (base32
                "1cnmn6c2dyl8qfl7g5sqwbjb52psqxzrj1mbm06zak2y1j7j8f49"))))
    (properties `((upstream-name . "AdvBinomApps")))
    (build-system r-build-system)
    (propagated-inputs (list r-rootsolve r-genbinomapps))
    (home-page "https://cran.r-project.org/package=AdvBinomApps")
    (synopsis
     "Upper Clopper-Pearson Confidence Limits for Burn-in Studies under Additional Available Information")
    (description
     "This package provides functions to compute upper Clopper-Pearson confidence
limits of early life failure probabilities and required sample sizes of burn-in
studies under further available information, e.g. from other products or
technologies.")
    (license license:gpl3)))

(define-public r-advancedbasketballstats
  (package
    (name "r-advancedbasketballstats")
    (version "1.0.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AdvancedBasketballStats" version))
              (sha256
               (base32
                "0wwqnijhz2sa3pcf8mjidw7m4awqgbsn4sgly93zyspb5fv7yblk"))))
    (properties `((upstream-name . "AdvancedBasketballStats")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=AdvancedBasketballStats")
    (synopsis "Advanced Basketball Statistics")
    (description
     "This package provides different functionalities and calculations used in the
world of basketball to analyze the statistics of the players, the statistics of
the teams, the statistics of the quintets and the statistics of the plays.  For
more details of the calculations included in the package can be found in the
book Basketball on Paper written by Dean Oliver.")
    (license license:gpl2+)))

(define-public r-adsdatahubr
  (package
    (name "r-adsdatahubr")
    (version "0.1.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "adsDataHubR" version))
              (sha256
               (base32
                "19csivbg3f0g2r11l7jrciqq2lhg50km7qv29xfs6ba5cf678hb9"))))
    (properties `((upstream-name . "adsDataHubR")))
    (build-system r-build-system)
    (propagated-inputs (list r-lubridate r-jsonlite r-httr))
    (home-page "https://cran.r-project.org/package=adsDataHubR")
    (synopsis "Google Ads Data Hub API Client")
    (description
     "Interact with Google Ads Data Hub API
<https://developers.google.com/ads-data-hub/reference/rest>.  The functionality
allows to fetch customer details, submit queries to ADH.")
    (license license:gpl2)))

(define-public r-ads
  (package
    (name "r-ads")
    (version "1.5-8")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ads" version))
              (sha256
               (base32
                "01iyjkxk2d86nl3kd498xaaw4b8y9l142pkbyr49w1h299d3d7f7"))))
    (properties `((upstream-name . "ads")))
    (build-system r-build-system)
    (propagated-inputs (list r-spatstat-geom r-ade4))
    (home-page "https://cran.r-project.org/package=ads")
    (synopsis "Spatial Point Patterns Analysis")
    (description
     "Perform first- and second-order multi-scale analyses derived from Ripley
K-function (Ripley B. D. (1977) <doi:10.1111/j.2517-6161.1977.tb01615.x>), for
univariate, multivariate and marked mapped data in rectangular, circular or
irregular shaped sampling windows, with tests of statistical significance based
on Monte Carlo simulations.")
    (license license:gpl2)))

(define-public r-adpss
  (package
    (name "r-adpss")
    (version "0.1.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "adpss" version))
              (sha256
               (base32
                "0p2gyfc4rxmms8zdsq4hjsh1njfl2s736arq8aq1am2wh1w9k5ch"))))
    (properties `((upstream-name . "adpss")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpp))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/ca4wa/R-adpss")
    (synopsis
     "Design and Analysis of Locally or Globally Efficient Adaptive Designs")
    (description
     "This package provides the functions for planning and conducting a clinical trial
with adaptive sample size determination.  Maximal statistical efficiency will be
exploited even when dramatic or multiple adaptations are made.  Such a trial
consists of adaptive determination of sample size at an interim analysis and
implementation of frequentist statistical test at the interim and final analysis
with a prefixed significance level.  The required assumptions for the stage-wise
test statistics are independent and stationary increments and normality.
Predetermination of adaptation rule is not required.")
    (license license:gpl2+)))

(define-public r-adpf
  (package
    (name "r-adpf")
    (version "0.0.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ADPF" version))
              (sha256
               (base32
                "1n7302xx77ngvp9i2h582i1mqslzllcdr0bn3pl2zk9jd8k97p7n"))))
    (properties `((upstream-name . "ADPF")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=ADPF")
    (synopsis
     "Use Least Squares Polynomial Regression and Statistical Testing to Improve Savitzky-Golay")
    (description
     "This function takes a vector or matrix of data and smooths the data with an
improved Savitzky Golay transform.  The Savitzky-Golay method for data smoothing
and differentiation calculates convolution weights using Gram polynomials that
exactly reproduce the results of least-squares polynomial regression.  Use of
the Savitzky-Golay method requires specification of both filter length and
polynomial degree to calculate convolution weights.  For maximum smoothing of
statistical noise in data, polynomials with low degrees are desirable, while a
high polynomial degree is necessary for accurate reproduction of peaks in the
data.  Extension of the least-squares regression formalism with statistical
testing of additional terms of polynomial degree to a heuristically chosen
minimum for each data window leads to an adaptive-degree polynomial filter
(ADPF).  Based on noise reduction for data that consist of pure noise and on
signal reproduction for data that is purely signal, ADPF performed nearly as
well as the optimally chosen fixed-degree Savitzky-Golay filter and outperformed
sub-optimally chosen Savitzky-Golay filters.  For synthetic data consisting of
noise and signal, ADPF outperformed both optimally chosen and sub-optimally
chosen fixed-degree Savitzky-Golay filters.  See Barak, P. (1995)
<doi:10.1021/ac00113a006> for more information.")
    (license license:gpl3)))

(define-public r-adpclust
  (package
    (name "r-adpclust")
    (version "0.7")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ADPclust" version))
              (sha256
               (base32
                "0s47cpsjykn7imsssa9w9b6g9d1sz2yah78yqzxmh0i3lqd757c1"))))
    (properties `((upstream-name . "ADPclust")))
    (build-system r-build-system)
    (propagated-inputs (list r-knitr r-fields r-dplyr r-cluster))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/ethanyxu/ADPclust")
    (synopsis "Fast Clustering Using Adaptive Density Peak Detection")
    (description
     "An implementation of ADPclust clustering procedures (Fast Clustering Using
Adaptive Density Peak Detection).  The work is built and improved upon the idea
of Rodriguez and Laio (2014)<DOI:10.1126/science.1242072>.  ADPclust clusters
data by finding density peaks in a density-distance plot generated from local
multivariate Gaussian density estimation.  It includes an automatic centroids
selection and parameter optimization algorithm, which finds the number of
clusters and cluster centroids by comparing average silhouettes on a grid of
testing clustering results; It also includes a user interactive algorithm that
allows the user to manually selects cluster centroids from a two dimensional
\"density-distance plot\".  Here is the research article associated with this
package: \"Wang, Xiao-Feng, and Yifan Xu (2015)<DOI:10.1177/0962280215609948>
Fast clustering using adaptive density peak detection.\" Statistical methods in
medical research\".  url:
http://smm.sagepub.com/content/early/2015/10/15/0962280215609948.abstract.")
    (license license:gpl2+)))

(define-public r-adp
  (package
    (name "r-adp")
    (version "0.1.6")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ADP" version))
              (sha256
               (base32
                "1ljm4bri3b96r544x3n37qrfm6krmij8yjfr8n5acllqp6jnf2d5"))))
    (properties `((upstream-name . "ADP")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=ADP")
    (synopsis "Adoption Probability, Triers and Users Rate of a New Product")
    (description
     "Calculate users prevalence of a product based on the prevalence of triers in the
population.  The measurement of triers is relatively easy.  It is just a
question of whether a person tried a product even once in his life or not.  On
the other hand, The measurement of people who also adopt it as part of their
life is more complicated since adopting an innovative product is a subjective
view of the individual.  Mickey Kislev and Shira Kislev developed a formula to
calculate the prevalence of a product's users to overcome this difficulty.  The
current package assists in calculating the users prevalence of a product based
on the prevalence of triers in the population.  See for: Kislev, M. M., and S.
Kislev (2020) <doi:10.5539/ijms.v12n4p63>.")
    (license license:gpl3)))

(define-public r-adoptr
  (package
    (name "r-adoptr")
    (version "1.0.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "adoptr" version))
              (sha256
               (base32
                "08d2fsqh5vczfr9cc8l554p6f0x85g58i5zg5j2m0chlmcispfk2"))))
    (properties `((upstream-name . "adoptr")))
    (build-system r-build-system)
    (propagated-inputs (list r-nloptr r-glue))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/kkmann/adoptr")
    (synopsis "Adaptive Optimal Two-Stage Designs in R")
    (description
     "Optimize one or two-arm, two-stage designs for clinical trials with respect to
several pre-implemented objective criteria or implement custom objectives.
Optimization under uncertainty and conditional (given stage-one outcome)
constraints are supported.  See <doi:10.1002/sim.8291> and
<doi:10.18637/jss.v098.i09> for details.")
    (license license:expat)))

(define-public r-adobeanalyticsr
  (package
    (name "r-adobeanalyticsr")
    (version "0.3.3")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "adobeanalyticsr" version))
              (sha256
               (base32
                "1x1mkprp42xyfgiyffkj9lwzfv79dfwdg9alxfcpmgcvcrnbxcwi"))))
    (properties `((upstream-name . "adobeanalyticsr")))
    (build-system r-build-system)
    (propagated-inputs (list r-vctrs
                             r-tidyr
                             r-tibble
                             r-stringr
                             r-scales
                             r-rlang
                             r-r6
                             r-purrr
                             r-progress
                             r-openssl
                             r-memoise
                             r-lubridate
                             r-lifecycle
                             r-jsonlite
                             r-jose
                             r-httr
                             r-glue
                             r-ggplot2
                             r-dplyr
                             r-assertthat))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/benrwoodard/adobeanalyticsr")
    (synopsis "R Client for 'Adobe Analytics' API 2.0")
    (description
     "Connect to the Adobe Analytics API v2.0
<https://github.com/AdobeDocs/analytics-2.0-apis> which powers Analysis
Workspace'.  The package was developed with the analyst in mind, and it will
continue to be developed with the guiding principles of iterative, repeatable,
timely analysis.")
    (license license:expat)))

(define-public r-adnuts
  (package
    (name "r-adnuts")
    (version "1.1.2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "adnuts" version))
              (sha256
               (base32
                "0nkciv5sfj3bws6kpgrnaq4ziasibaz44w64mb86zmr8420nyc1q"))))
    (properties `((upstream-name . "adnuts")))
    (build-system r-build-system)
    (propagated-inputs (list r-snowfall
                             r-rstan
                             r-rlang
                             r-r2admb
                             r-ggplot2
                             r-ellipse))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/Cole-Monnahan-NOAA/adnuts")
    (synopsis "No-U-Turn MCMC Sampling for 'ADMB' Models")
    (description
     "Bayesian inference using the no-U-turn (NUTS) algorithm by Hoffman and Gelman
(2014) <https://www.jmlr.org/papers/v15/hoffman14a.html>.  Designed for AD Model
Builder ('ADMB') models, or when R functions for log-density and log-density
gradient are available, such as Template Model Builder models and other special
cases.  Functionality is similar to Stan', and the rstan and shinystan packages
are used for diagnostics and inference.")
    (license (list license:gpl3
                   (license:fsdg-compatible "file://LICENSE")))))

(define-public r-admur
  (package
    (name "r-admur")
    (version "1.0.3")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ADMUR" version))
              (sha256
               (base32
                "1wv5frav8vjkvsqwng9zddajmb7rdm4iqrikw9cjpqdpk7njl8ph"))))
    (properties `((upstream-name . "ADMUR")))
    (build-system r-build-system)
    (propagated-inputs (list r-zoo r-scales r-mathjaxr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/UCL/ADMUR")
    (synopsis "Ancient Demographic Modelling Using Radiocarbon")
    (description
     "This package provides tools to directly model underlying population dynamics
using date datasets (radiocarbon and other) with a Continuous Piecewise Linear
(CPL) model framework.  Various other model types included.  Taphonomic loss
included optionally as a power function.  Model comparison framework using BIC.
Package also calibrates 14C samples, generates Summed Probability Distributions
(SPD), and performs SPD simulation analysis to generate a Goodness-of-fit test
for the best selected model.  Details about the method can be found in Timpson
A., Barberena R., Thomas M. G., Mendez C., Manning K. (2020)
<doi:10.1098/rstb.2019.0723>.")
    (license license:gpl3)))

(define-public r-admmsigma
  (package
    (name "r-admmsigma")
    (version "2.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ADMMsigma" version))
              (sha256
               (base32
                "1943dza086s22pr0yz41wzn9cdg11x7fl9zr3w012865yj219m7l"))))
    (properties `((upstream-name . "ADMMsigma")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcppprogress
                             r-rcpparmadillo
                             r-rcpp
                             r-ggplot2
                             r-foreach
                             r-dplyr
                             r-doparallel))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/MGallow/ADMMsigma")
    (synopsis "Penalized Precision Matrix Estimation via ADMM")
    (description
     "Estimates a penalized precision matrix via the alternating direction method of
multipliers (ADMM) algorithm.  It currently supports a general elastic-net
penalty that allows for both ridge and lasso-type penalties as special cases.
This package is an alternative to the glasso package.  See Boyd et al (2010)
<doi:10.1561/2200000016> for details regarding the estimation method.")
    (license license:gpl2+)))

(define-public r-admmnet
  (package
    (name "r-admmnet")
    (version "0.1.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ADMMnet" version))
              (sha256
               (base32
                "1la92fwg75ylqbz00znqd0rhv5r509kgh9wwznjacppif773wp6i"))))
    (properties `((upstream-name . "ADMMnet")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcppeigen r-rcpp r-matrix))
    (home-page "https://cran.r-project.org/package=ADMMnet")
    (synopsis "Regularized Model with Selecting the Number of Non-Zeros")
    (description
     "Fit linear and cox models regularized with net (L1 and Laplacian), elastic-net
(L1 and L2) or lasso (L1) penalty, and their adaptive forms, such as adaptive
lasso and net adjusting for signs of linked coefficients.  In addition, it
treats the number of non-zero coefficients as another tuning parameter and
simultaneously selects with the regularization parameter.  The package uses
one-step coordinate descent algorithm and runs extremely fast by taking into
account the sparsity structure of coefficients.")
    (license license:gpl2+)))

(define-public r-admmdensestsubmatrix
  (package
    (name "r-admmdensestsubmatrix")
    (version "0.1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "admmDensestSubmatrix" version))
              (sha256
               (base32
                "1a5lfm10aj6wdjibdnmffn75zvy6x69w8nqcx2i23gxg6v0xlqcl"))))
    (properties `((upstream-name . "admmDensestSubmatrix")))
    (build-system r-build-system)
    (propagated-inputs (list r-rdpack))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=admmDensestSubmatrix")
    (synopsis
     "Alternating Direction Method of Multipliers to Solve Dense Dubmatrix Problem")
    (description
     "Solves the problem of identifying the densest submatrix in a given or sampled
binary matrix, Bombina et al. (2019) <arXiv:1904.03272>.")
    (license license:cc0)))

(define-public r-admm
  (package
    (name "r-admm")
    (version "0.3.3")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ADMM" version))
              (sha256
               (base32
                "04biinzr0x3jkwss00q6zxfnzk62dafc6386z5vfqs4ch0ifh60n"))))
    (properties `((upstream-name . "ADMM")))
    (build-system r-build-system)
    (propagated-inputs (list r-rdpack
                             r-rcpparmadillo
                             r-rcpp
                             r-matrix
                             r-foreach
                             r-doparallel))
    (home-page "https://cran.r-project.org/package=ADMM")
    (synopsis "Algorithms using Alternating Direction Method of Multipliers")
    (description
     "This package provides algorithms to solve popular optimization problems in
statistics such as regression or denoising based on Alternating Direction Method
of Multipliers (ADMM).  See Boyd et al (2010) <doi:10.1561/2200000016> for
complete introduction to the method.")
    (license license:gpl3+)))

(define-public r-admixr
  (package
    (name "r-admixr")
    (version "0.9.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "admixr" version))
              (sha256
               (base32
                "0wszpzs53cbnha13g2ldpq6z5ndw2v2xgrzadqkjm3hsp6akv4bl"))))
    (properties `((upstream-name . "admixr")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble
                             r-stringr
                             r-rlang
                             r-readr
                             r-magrittr
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/bodkan/admixr")
    (synopsis "An Interface for Running 'ADMIXTOOLS' Analyses")
    (description
     "An interface for performing all stages of ADMIXTOOLS analyses
(<https://reich.hms.harvard.edu/software>) entirely from R. Wrapper functions
(D, f4, f3, etc.) completely automate the generation of intermediate
configuration files, run ADMIXTOOLS programs on the command-line, and parse
output files to extract values of interest.  This allows users to focus on the
analysis itself instead of worrying about low-level technical details.  A set of
complementary functions for processing and filtering of data in the EIGENSTRAT
format is also provided.")
    (license license:expat)))

(define-public r-admix
  (package
    (name "r-admix")
    (version "0.4.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "admix" version))
              (sha256
               (base32
                "1vfga2l6yay4l8q53siibf1ljr77fmcgbddlag414jmv2awckr0c"))))
    (properties `((upstream-name . "admix")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpp
                             r-pracma
                             r-orthopolynom
                             r-mass
                             r-latex2exp
                             r-iso
                             r-fdrtool))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/XavierMilhaud/admix")
    (synopsis "Package Admix for Admixture (aka Contamination) Models")
    (description
     "This package implements several methods to estimate the unknown quantities
related to two-component admixture models, where the two components can belong
to any distribution (note that in the case of multinomial mixtures, the two
components must belong to the same family).  Estimation methods depend on the
assumptions made on the unknown component density (see Bordes and Vandekerkhove
(2010) <doi:10.3103/S1066530710010023>; Patra and Sen (2016)
<doi:10.1111/rssb.12148>); Milhaud, Pommeret, Salhi and Vandekerkhove (2021)
<doi:10.1016/j.jspi.2021.05.010>).  In practice, one can estimate both the
mixture weight and the unknown component density in a wide variety of
frameworks.  On top of that, hypothesis tests can be performed in one and
two-samples contexts to test the unknown component density.  Finally, clustering
of unknown mixture components is also feasible in a K-samples setting.")
    (license license:gpl3+)))

(define-public r-admit
  (package
    (name "r-admit")
    (version "2.1.9")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AdMit" version))
              (sha256
               (base32
                "0dlmqpwqfhhc4z2xr44f00xsg0hbmw2c5z2d4pbifv36jlrdxbip"))))
    (properties `((upstream-name . "AdMit")))
    (build-system r-build-system)
    (propagated-inputs (list r-mvtnorm))
    (home-page "https://github.com/ArdiaD/AdMit")
    (synopsis "Adaptive Mixture of Student-t Distributions")
    (description
     "This package provides functions to perform the fitting of an adaptive mixture of
Student-t distributions to a target density through its kernel function as
described in Ardia et al. (2009) <doi:10.18637/jss.v029.i03>.  The mixture
approximation can then be used as the importance density in importance sampling
or as the candidate density in the Metropolis-Hastings algorithm to obtain
quantities of interest for the target density itself.")
    (license license:gpl2+)))

(define-public r-admiralonco
  (package
    (name "r-admiralonco")
    (version "0.1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "admiralonco" version))
              (sha256
               (base32
                "17c52zaqw3p9bd4gi93rbam367rldp12xsk1ayl4dyxyamazcksg"))))
    (properties `((upstream-name . "admiralonco")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyselect
                             r-rlang
                             r-magrittr
                             r-lubridate
                             r-dplyr
                             r-admiraldev
                             r-admiral))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=admiralonco")
    (synopsis "Oncology Extension Package for ADaM in 'R' Asset Library")
    (description
     "Programming oncology specific Clinical Data Interchange Standards Consortium
(CDISC) compliant Analysis Data Model (ADaM) datasets in R'.  ADaM datasets are
a mandatory part of any New Drug or Biologics License Application submitted to
the United States Food and Drug Administration (FDA).  Analysis derivations are
implemented in accordance with the \"Analysis Data Model Implementation Guide\"
(CDISC Analysis Data Model Team (2021),
<https://www.cdisc.org/standards/foundational/adam/adamig-v1-3-release-package>).
 The package is an extension package of the admiral package.")
    (license (license:fsdg-compatible "Apache License (>= 2)"))))

(define-public r-admiraldev
  (package
    (name "r-admiraldev")
    (version "0.2.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "admiraldev" version))
              (sha256
               (base32
                "0rclhf3d2mhsbxc4imp14kpjxw6g0hdy6v4y86qnvvyrb3cik46v"))))
    (properties `((upstream-name . "admiraldev")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyselect
                             r-tidyr
                             r-stringr
                             r-rlang
                             r-purrr
                             r-magrittr
                             r-lubridate
                             r-lifecycle
                             r-hms
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://pharmaverse.github.io/admiraldev/main/")
    (synopsis "Development Tools for the Admiral Package Family")
    (description
     "Utility functions to check data, variables and conditions for functions used in
admiral and admiral extension packages.  Additional utility helper functions to
assist developers with maintaining documentation, testing and general upkeep of
admiral and admiral extension packages.")
    (license (license:fsdg-compatible "Apache License (>= 2)"))))

(define-public r-admiral-test
  (package
    (name "r-admiral-test")
    (version "0.4.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "admiral.test" version))
              (sha256
               (base32
                "1abf7zrqj2bia784rvl3y4awyi3vpaj57lqyak2zpxiykhs8fg4s"))))
    (properties `((upstream-name . "admiral.test")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=admiral.test")
    (synopsis "Test Data for the 'admiral' Package")
    (description
     "This package provides a set of Study Data Tabulation Model (SDTM) datasets from
the Clinical Data Interchange Standards Consortium (CDISC) pilot project used
for testing and developing Analysis Data Model (ADaM) derivations inside the
admiral package.")
    (license (license:fsdg-compatible "Apache License (>= 2.0)"))))

(define-public r-admiral
  (package
    (name "r-admiral")
    (version "0.8.4")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "admiral" version))
              (sha256
               (base32
                "0d7ikgxyvb14p3g3vjjkqhr5yhm7pa3wfr9mb3ann42lnzn5950b"))))
    (properties `((upstream-name . "admiral")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyselect
                             r-tidyr
                             r-stringr
                             r-rlang
                             r-purrr
                             r-magrittr
                             r-lubridate
                             r-lifecycle
                             r-hms
                             r-dplyr
                             r-assertthat
                             r-admiraldev))
    (native-inputs (list r-knitr))
    (home-page "https://pharmaverse.github.io/admiral/")
    (synopsis "ADaM in R Asset Library")
    (description
     "This package provides a toolbox for programming Clinical Data Interchange
Standards Consortium (CDISC) compliant Analysis Data Model (ADaM) datasets in R.
ADaM datasets are a mandatory part of any New Drug or Biologics License
Application submitted to the United States Food and Drug Administration (FDA).
Analysis derivations are implemented in accordance with the \"Analysis Data Model
Implementation Guide\" (CDISC Analysis Data Model Team, 2021,
<https://www.cdisc.org/standards/foundational/adam/adamig-v1-3-release-package>).")
    (license (license:fsdg-compatible "Apache License (>= 2)"))))

(define-public r-adlift
  (package
    (name "r-adlift")
    (version "1.4-4")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "adlift" version))
              (sha256
               (base32
                "1rxwsmic17kgbhh50m87mh8ag8l6b1n4p96k0qn6mkgqfiqngam5"))))
    (properties `((upstream-name . "adlift")))
    (build-system r-build-system)
    (propagated-inputs (list r-ebayesthresh))
    (home-page "https://cran.r-project.org/package=adlift")
    (synopsis "An Adaptive Lifting Scheme Algorithm")
    (description
     "Adaptive wavelet lifting transforms for signal denoising using optimal local
neighbourhood regression, from Nunes et al. (2006)
<doi:10.1007/s11222-006-6560-y>.")
    (license (list license:gpl2+ license:gpl3+))))

(define-public r-adklakedata
  (package
    (name "r-adklakedata")
    (version "0.6.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "adklakedata" version))
              (sha256
               (base32
                "1lzj3ib4bgfkq5lq12n47pwc52h7k35xbbwj6brwsgx1gd4fx3x6"))))
    (properties `((upstream-name . "adklakedata")))
    (build-system r-build-system)
    (propagated-inputs (list r-rappdirs r-httr))
    (home-page "https://cran.r-project.org/package=adklakedata")
    (synopsis "Adirondack Long-Term Lake Data")
    (description
     "Package for the access and distribution of Long-term lake datasets from lakes in
the Adirondack Park, northern New York state.  Includes a wide variety of
physical, chemical, and biological parameters from 28 lakes.  Data are from
multiple collection organizations and have been harmonized in both time and
space for ease of reuse.")
    (license license:expat)))

(define-public r-adjustedcurves
  (package
    (name "r-adjustedcurves")
    (version "0.9.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "adjustedCurves" version))
              (sha256
               (base32
                "1mhl4mzw4286kp9khlv2kpfvzhnvwkmdicwc0z7mlqyi46znylib"))))
    (properties `((upstream-name . "adjustedCurves")))
    (build-system r-build-system)
    (propagated-inputs (list r-rlang
                             r-r-utils
                             r-foreach
                             r-dplyr
                             r-dorng
                             r-doparallel))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/RobinDenz1/adjustedCurves")
    (synopsis
     "Confounder-Adjusted Survival Curves and Cumulative Incidence Functions")
    (description
     "Estimate and plot confounder-adjusted survival curves using either Direct
Adjustment', Direct Adjustment with Pseudo-Values', various forms of Inverse
Probability of Treatment Weighting', two forms of Augmented Inverse Probability
of Treatment Weighting', Empirical Likelihood Estimation and Targeted Maximum
Likelihood Estimation'.  Also includes a significance test for the difference
between two adjusted survival curves and the calculation of adjusted restricted
mean survival times.  Additionally enables the user to estimate and plot
cause-specific confounder-adjusted cumulative incidence functions in the
competing risks setting using the same methods (with some exceptions).  For
details, see Denz et.  al (2022) <arXiv:2203.10002v1>.")
    (license license:gpl3+)))

(define-public r-adjustedcranlogs
  (package
    (name "r-adjustedcranlogs")
    (version "0.1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "adjustedcranlogs" version))
              (sha256
               (base32
                "08apfvpqvnnalx230p4qf5ckrwm1sgzras4zfrysgym5d4map9ci"))))
    (properties `((upstream-name . "adjustedcranlogs")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml2 r-rvest r-lubridate r-dplyr r-cranlogs))
    (home-page "https://github.com/tylermorganwall/adjustedcranlogs")
    (synopsis
     "Remove Automated and Repeated Downloads from 'RStudio' 'CRAN' Download Logs")
    (description
     "Adjusts output of cranlogs package to account for CRAN'-wide daily automated
downloads and re-downloads caused by package updates.")
    (license license:expat)))

(define-public r-adjsurvci
  (package
    (name "r-adjsurvci")
    (version "1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "adjSURVCI" version))
              (sha256
               (base32
                "0nv6m7ds57d0h44d745s0424ssrgn39ihd294dgrzrpmh8gxhq95"))))
    (properties `((upstream-name . "adjSURVCI")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival r-rcpparmadillo r-rcpp))
    (home-page "https://cran.r-project.org/package=adjSURVCI")
    (synopsis
     "Parameter and Adjusted Probability Estimation for Right-Censored Data")
    (description
     "This package provides functions in this package fit a stratified Cox
proportional hazards and a proportional subdistribution hazards model by
extending Zhang et al., (2007) <doi: 10.1016/j.cmpb.2007.07.010> and Zhang et
al., (2011) <doi: 10.1016/j.cmpb.2010.07.005> respectively to clustered
right-censored data.  The functions also provide the estimates of the cumulative
baseline hazard along with their standard errors.  Furthermore, the adjusted
survival and cumulative incidence probabilities are also provided along with
their standard errors.  Finally, the estimate of cumulative incidence and
survival probabilities given a vector of covariates along with their standard
errors are also provided.")
    (license license:gpl2+)))

(define-public r-adjroc
  (package
    (name "r-adjroc")
    (version "0.2.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "adjROC" version))
              (sha256
               (base32
                "0ipvp7f7asg8pbzbm3rnn8hp20gs3aqispvagddjw1yd39h0zgrk"))))
    (properties `((upstream-name . "adjROC")))
    (build-system r-build-system)
    (propagated-inputs (list r-rocit r-ggplot2))
    (home-page "https://github.com/haghish/adjROC")
    (synopsis
     "Computing Sensitivity at a Fix Value of Specificity and Vice Versa")
    (description
     "For a binary classification the adjusted sensitivity and specificity are
measured for a given fixed threshold.  If the threshold for either sensitivity
or specificity is not given, the crossing point between the sensitivity and
specificity curves are returned.")
    (license license:expat)))

(define-public r-adjclust
  (package
    (name "r-adjclust")
    (version "0.6.6")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "adjclust" version))
              (sha256
               (base32
                "0kin57r12g1cv4pi6br3c71rpjhfvpkysx7jly3wf0ilj6bfs6vk"))))
    (properties `((upstream-name . "adjclust")))
    (build-system r-build-system)
    (propagated-inputs (list r-sparsematrixstats r-rcpparmadillo r-rcpp
                             r-matrix r-capushe))
    (native-inputs (list r-knitr))
    (home-page "https://pneuvial.github.io/adjclust/")
    (synopsis
     "Adjacency-Constrained Clustering of a Block-Diagonal Similarity Matrix")
    (description
     "This package implements a constrained version of hierarchical agglomerative
clustering, in which each observation is associated to a position, and only
adjacent clusters can be merged.  Typical application fields in bioinformatics
include Genome-Wide Association Studies or Hi-C data analysis, where the
similarity between items is a decreasing function of their genomic distance.
Taking advantage of this feature, the implemented algorithm is time and memory
efficient.  This algorithm is described in Ambroise et al (2019)
<https://almob.biomedcentral.com/articles/10.1186/s13015-019-0157-4>.")
    (license license:gpl3)))

(define-public r-adiv
  (package
    (name "r-adiv")
    (version "2.2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "adiv" version))
              (sha256
               (base32
                "0qmykswwirhas4rrwb4jaqicjkqsmq6k11718hzk65h3xdnpg6kr"))))
    (properties `((upstream-name . "adiv")))
    (build-system r-build-system)
    (propagated-inputs (list r-rgl
                             r-phytools
                             r-phylobase
                             r-lpsolve
                             r-cluster
                             r-ape
                             r-adegraphics
                             r-ade4))
    (home-page "https://cran.r-project.org/package=adiv")
    (synopsis "Analysis of Diversity")
    (description
     "Functions, data sets and examples for the calculation of various indices of
biodiversity including species, functional and phylogenetic diversity.  Part of
the indices are expressed in terms of equivalent numbers of species.  The
package also provides ways to partition biodiversity across spatial or temporal
scales (alpha, beta, gamma diversities).  In addition to the quantification of
biodiversity, ordination approaches are available which rely on diversity
indices and allow the detailed identification of species, functional or
phylogenetic differences between communities.")
    (license license:gpl2+)))

(define-public r-adhererviz
  (package
    (name "r-adhererviz")
    (version "0.2.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AdhereRViz" version))
              (sha256
               (base32
                "1jc5mfdydw9s515zi7lsmns79919vrdhh6lvh9z2bq0lrn9g1yci"))))
    (properties `((upstream-name . "AdhereRViz")))
    (build-system r-build-system)
    (propagated-inputs (list r-viridislite
                             r-v8
                             r-shinywidgets
                             r-shinyjs
                             r-shiny
                             r-rsqlite
                             r-rmariadb
                             r-manipulate
                             r-knitr
                             r-highlight
                             r-dbi
                             r-data-table
                             r-colourpicker
                             r-clipr
                             r-adherer))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/ddediu/AdhereR")
    (synopsis "Adherence to Medications")
    (description
     "Interactive graphical user interface (GUI) for the package AdhereR', allowing
the user to access different data sources, to explore the patterns of medication
use therein, and the computation of various measures of adherence.  It is
implemented using Shiny and HTML/CSS/JavaScript.")
    (license license:gpl2+)))

(define-public r-adherer
  (package
    (name "r-adherer")
    (version "0.8.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AdhereR" version))
              (sha256
               (base32
                "0b98yz2msg30ch3n85yzi42rlnyj5ggkz1fsysh95gd5qk4c8vg2"))))
    (properties `((upstream-name . "AdhereR")))
    (build-system r-build-system)
    (propagated-inputs (list r-webp
                             r-rsvg
                             r-png
                             r-lubridate
                             r-jpeg
                             r-data-table))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/ddediu/AdhereR")
    (synopsis "Adherence to Medications")
    (description
     "Computation of adherence to medications from Electronic Health care Data and
visualization of individual medication histories and adherence patterns.  The
package implements a set of S3 classes and functions consistent with current
adherence guidelines and definitions.  It allows the computation of different
measures of adherence (as defined in the literature, but also several original
ones), their publication-quality plotting, the estimation of event duration and
time to initiation, the interactive exploration of patient medication history
and the real-time estimation of adherence given various parameter settings.  It
scales from very small datasets stored in flat CSV files to very large databases
and from single-thread processing on mid-range consumer laptops to parallel
processing on large heterogeneous computing clusters.  It exposes a standardized
interface allowing it to be used from other programming languages and platforms,
such as Python.")
    (license license:gpl2+)))

(define-public r-adherencerx
  (package
    (name "r-adherencerx")
    (version "1.0.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "adheRenceRX" version))
              (sha256
               (base32
                "19kimj88dmcc8mq3s4l7pph9jz8p57gbjyn0pn5zkrcjdrwncslm"))))
    (properties `((upstream-name . "adheRenceRX")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-rlang
                             r-rcpp
                             r-purrr
                             r-lubridate
                             r-dplyr
                             r-anytime))
    (home-page "https://github.com/btbeal/adheRenceRX")
    (synopsis "Assess Medication Adherence from Pharmaceutical Claims Data")
    (description
     "This package provides a (mildly) opinionated set of functions to help assess
medication adherence for researchers working with medication claims data.
Medication adherence analyses have several complex steps that are often
convoluted and can be time-intensive.  The focus is to create a set of functions
using \"tidy principles\" geared towards transparency, speed, and flexibility
while working with adherence metrics.  All functions perform exactly one task
with an intuitive name so that a researcher can handle details (often achieved
with vectorized solutions) while we handle non-vectorized tasks common to most
adherence calculations such as adjusting fill dates and determining episodes of
care.  The methodologies in referenced in this package come from Canfield SL, et
al (2019) \"Navigating the Wild West of Medication Adherence Reporting in
Specialty Pharmacy\" <doi:10.18553/jmcp.2019.25.10.1073>.")
    (license license:gpl2+)))

(define-public r-adformr
  (package
    (name "r-adformr")
    (version "0.1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "adformR" version))
              (sha256
               (base32
                "02krkpqsj53j4mprbw25bycbb2xlhcgnglcp0dl24zw44mfxy9n7"))))
    (properties `((upstream-name . "adformR")))
    (build-system r-build-system)
    (propagated-inputs (list r-jsonlite))
    (native-inputs (list r-knitr))
    (home-page "https://windsor.ai/")
    (synopsis "Get Adform Ads Data via the 'Windsor.ai' API")
    (description
     "Collect your data on digital marketing campaigns from Adform Ads using the
Windsor.ai API <https://windsor.ai/api-fields/>.")
    (license license:gpl3)))

(define-public r-adfexplorer
  (package
    (name "r-adfexplorer")
    (version "0.1.6")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "adfExplorer" version))
              (sha256
               (base32
                "06sk68580i7jg9lk4jj64ns04y4q6amzsh0k7nxhfdib107yajnp"))))
    (properties `((upstream-name . "adfExplorer")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://github.com/pepijn-devries/adfExplorer")
    (synopsis "Import from and Export to Amiga Disk Files")
    (description
     "Amiga Disk Files (ADF) are virtual representations of 3.5 inch floppy disks for
the Commodore Amiga.  Most disk drives from other systems (including modern
drives) are not able to read these disks.  To be able to emulate this system,
the ADF format was created.  This package enables you to read ADF files and
import and export files from and to such virtual DOS-formatted disks.")
    (license license:gpl3)))

(define-public r-adespatial
  (package
    (name "r-adespatial")
    (version "0.3-20")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "adespatial" version))
              (sha256
               (base32
                "1sv4kc30l226x24s3gvv8dq0p2y33h8vv474bfpm4z08cfah13pq"))))
    (properties `((upstream-name . "adespatial")))
    (build-system r-build-system)
    (propagated-inputs (list r-vegan
                             r-spdep
                             r-sp
                             r-shiny
                             r-mass
                             r-lattice
                             r-adephylo
                             r-adegraphics
                             r-ade4))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/sdray/adespatial")
    (synopsis "Multivariate Multiscale Spatial Analysis")
    (description
     "Tools for the multiscale spatial analysis of multivariate data.  Several methods
are based on the use of a spatial weighting matrix and its eigenvector
decomposition (Moran's Eigenvectors Maps, MEM).  Several approaches are
described in the review Dray et al (2012) <doi:10.1890/11-1183.1>.")
    (license license:gpl2+)))

(define-public r-ader
  (package
    (name "r-ader")
    (version "1.4")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ADER" version))
              (sha256
               (base32
                "0ada3b0ykbg1pdqj8i3ir5ldzb2prf3bhwm2mpln14h19hxc6i35"))))
    (properties `((upstream-name . "ADER")))
    (build-system r-build-system)
    (home-page "https://www.paraninfo.es/catalogo/9788484767053")
    (synopsis "Data Analysis in Ecology")
    (description
     "Data sets used in Cayuela and De la Cruz (2022, ISBN:978-84-8476-705-3).")
    (license license:gpl2+)))

(define-public r-adequacymodel
  (package
    (name "r-adequacymodel")
    (version "2.0.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AdequacyModel" version))
              (sha256
               (base32
                "0amp6ic1wylk24sp9wpx3ci38njj7b9qjqfp89j39hkl6kc1q7sq"))))
    (properties `((upstream-name . "AdequacyModel")))
    (build-system r-build-system)
    (home-page "http://www.r-project.org")
    (synopsis
     "Adequacy of Probabilistic Models and General Purpose Optimization")
    (description
     "The main application concerns to a new robust optimization package with two
major contributions.  The first contribution refers to the assessment of the
adequacy of probabilistic models through a combination of several statistics,
which measure the relative quality of statistical models for a given data set.
The second one provides a general purpose optimization method based on
meta-heuristics functions for maximizing or minimizing an arbitrary objective
function.")
    (license license:gpl2+)))

(define-public r-adeptdata
  (package
    (name "r-adeptdata")
    (version "1.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "adeptdata" version))
              (sha256
               (base32
                "0wzavbwc1slyr3wh5jkapghpa748rc86pbw5b4gcxki73r08r7j2"))))
    (properties `((upstream-name . "adeptdata")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=adeptdata")
    (synopsis "Accelerometry Data Sets")
    (description
     "Created to host raw accelerometry data sets and their derivatives which are used
in the corresponding adept package.")
    (license license:gpl3)))

(define-public r-adept
  (package
    (name "r-adept")
    (version "1.2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "adept" version))
              (sha256
               (base32
                "1dpfmfnqzci6p7wqwpp8y0cisx11r8kdsqjm85skb512n35m0i3a"))))
    (properties `((upstream-name . "adept")))
    (build-system r-build-system)
    (propagated-inputs (list r-pracma r-magrittr r-dvmisc r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/martakarass/adept")
    (synopsis "Adaptive Empirical Pattern Transformation")
    (description
     "Designed for optimal use in performing fast, accurate walking strides
segmentation from high-density data collected from a wearable accelerometer worn
during continuous walking activity.")
    (license license:gpl3)))

(define-public r-adepro
  (package
    (name "r-adepro")
    (version "3.2.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "adepro" version))
              (sha256
               (base32
                "0sw42yld4bjgfiqm957ply605zsj66mmwvkzi73hsbkk31w1k5fb"))))
    (properties `((upstream-name . "adepro")))
    (build-system r-build-system)
    (propagated-inputs (list r-v8
                             r-tidyr
                             r-teachingdemos
                             r-shinywidgets
                             r-shinyjs
                             r-shinybs
                             r-shiny
                             r-shape
                             r-seriation
                             r-rlang
                             r-readr
                             r-mass
                             r-jsonlite
                             r-haven
                             r-gclus
                             r-dplyr
                             r-cairo
                             r-audio))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=adepro")
    (synopsis
     "'shiny' Application for the (Audio-)Visualization of Adverse Event Profiles")
    (description
     "This package contains a shiny application called AdEPro (Animation of Adverse
Event Profiles) which (audio-)visualizes adverse events occurring in clinical
trials.  As this data is usually considered sensitive, this tool is provided as
a stand-alone application that can be launched from any local machine on which
the data is stored.")
    (license license:gpl3)))

(define-public r-adephylo
  (package
    (name "r-adephylo")
    (version "1.1-13")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "adephylo" version))
              (sha256
               (base32
                "0vd7khqsfnik7j00hac97khv8b1kmi0az5hakg04m8fhx7z3589a"))))
    (properties `((upstream-name . "adephylo")))
    (build-system r-build-system)
    (propagated-inputs (list r-phylobase r-ape r-adegenet r-ade4))
    (home-page "https://cran.r-project.org/package=adephylo")
    (synopsis "Exploratory Analyses for the Phylogenetic Comparative Method")
    (description
     "Multivariate tools to analyze comparative data, i.e.  a phylogeny and some
traits measured for each taxa.")
    (license license:gpl2+)))

(define-public r-adehabitatma
  (package
    (name "r-adehabitatma")
    (version "0.3.15")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "adehabitatMA" version))
              (sha256
               (base32
                "1j1idpr0704x3s9dhzxysr3zkm9lp6wnac1jdp98vvbd0l5h7icc"))))
    (properties `((upstream-name . "adehabitatMA")))
    (build-system r-build-system)
    (propagated-inputs (list r-sp))
    (home-page "https://cran.r-project.org/package=adehabitatMA")
    (synopsis "Tools to Deal with Raster Maps")
    (description
     "This package provides a collection of tools to deal with raster maps.")
    (license license:gpl2+)))

(define-public r-adehabitatlt
  (package
    (name "r-adehabitatlt")
    (version "0.3.26")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "adehabitatLT" version))
              (sha256
               (base32
                "0208qi802rn8ys00js843ckhg5pw20c55bz8b95kcl538grn9fs0"))))
    (properties `((upstream-name . "adehabitatLT")))
    (build-system r-build-system)
    (propagated-inputs (list r-sp r-circstats r-adehabitatma r-ade4))
    (home-page "https://cran.r-project.org/package=adehabitatLT")
    (synopsis "Analysis of Animal Movements")
    (description
     "This package provides a collection of tools for the analysis of animal
movements.")
    (license license:gpl2+)))

(define-public r-adehabitaths
  (package
    (name "r-adehabitaths")
    (version "0.3.16")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "adehabitatHS" version))
              (sha256
               (base32
                "1983k2819khkbr50v19n2k0jff9q8bcn1gqv4nmy2z8f24s43mnk"))))
    (properties `((upstream-name . "adehabitatHS")))
    (build-system r-build-system)
    (propagated-inputs (list r-sp r-adehabitatma r-adehabitathr r-ade4))
    (home-page "https://cran.r-project.org/package=adehabitatHS")
    (synopsis "Analysis of Habitat Selection by Animals")
    (description
     "This package provides a collection of tools for the analysis of habitat
selection.")
    (license license:gpl2+)))

(define-public r-adehabitathr
  (package
    (name "r-adehabitathr")
    (version "0.4.20")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "adehabitatHR" version))
              (sha256
               (base32
                "06r07cldrdm3d3kig55vvg505j82c0h38cip8rkgaxc29bf32bfx"))))
    (properties `((upstream-name . "adehabitatHR")))
    (build-system r-build-system)
    (propagated-inputs (list r-sp r-deldir r-adehabitatma r-adehabitatlt
                             r-ade4))
    (home-page "https://cran.r-project.org/package=adehabitatHR")
    (synopsis "Home Range Estimation")
    (description
     "This package provides a collection of tools for the estimation of animals home
range.")
    (license license:gpl2+)))

(define-public r-adegraphics
  (package
    (name "r-adegraphics")
    (version "1.0-16")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "adegraphics" version))
              (sha256
               (base32
                "0fpch8mffac68b64gh8jah8k9zcg8pphi38i9ddw5qggmvlrr9bv"))))
    (properties `((upstream-name . "adegraphics")))
    (build-system r-build-system)
    (propagated-inputs (list r-sp
                             r-rcolorbrewer
                             r-latticeextra
                             r-lattice
                             r-kernsmooth
                             r-ade4))
    (native-inputs (list r-knitr))
    (home-page "http://pbil.univ-lyon1.fr/ADE-4/")
    (synopsis
     "An S4 Lattice-Based Package for the Representation of Multivariate Data")
    (description
     "Graphical functionalities for the representation of multivariate data.  It is a
complete re-implementation of the functions available in the ade4 package.")
    (license license:gpl2+)))

(define-public r-adea
  (package
    (name "r-adea")
    (version "1.3.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "adea" version))
              (sha256
               (base32
                "0jvxgqwfga4gsn5jcdklfq2qci3xyvmkdfjappjwf72swb2rkv0n"))))
    (properties `((upstream-name . "adea")))
    (build-system r-build-system)
    (propagated-inputs (list r-rmarkdown r-lpsolveapi r-knitr r-combinat
                             r-benchmarking))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=adea")
    (synopsis "Alternate DEA Package")
    (description
     "The meaning of adea is \"alternate DEA\".  This package is devoted to provide the
alternative method of DEA described in the paper entitled \"Stepwise Selection of
Variables in DEA Using Contribution Load\", by F. Fernandez-Palacin, M. A.
Lopez-Sanchez and M. Munoz-Marquez.  Pesquisa Operacional 38 (1), pg.  1-24,
2018. <doi:10.1590/0101-7438.2018.038.01.0031>.  A full functional on-line and
interactive version is available at <https://knuth.uca.es/shiny/DEA/>.")
    (license license:gpl3+)))

(define-public r-ade4tkgui
  (package
    (name "r-ade4tkgui")
    (version "0.3-1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ade4TkGUI" version))
              (sha256
               (base32
                "1y0f62n8iv002ayd1nyl3bmszw558niwnfzjpvk0a7cbvfdyvwcg"))))
    (properties `((upstream-name . "ade4TkGUI")))
    (build-system r-build-system)
    (propagated-inputs (list r-lattice r-adegraphics r-ade4))
    (home-page "http://pbil.univ-lyon1.fr/ade4TkGUI/")
    (synopsis "'ade4' Tcl/Tk Graphical User Interface")
    (description
     "This package provides a Tcl/Tk GUI for some basic functions in the ade4 package.")
    (license license:gpl2+)))

(define-public r-addt
  (package
    (name "r-addt")
    (version "2.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ADDT" version))
              (sha256
               (base32
                "044bb1jw2m8vwk5q8l7rlz4kqphjvy8i9d59rjg0k5q5l9vczfrp"))))
    (properties `((upstream-name . "ADDT")))
    (build-system r-build-system)
    (propagated-inputs (list r-nlme r-matrix r-coneproj))
    (home-page "https://cran.r-project.org/package=ADDT")
    (synopsis "Analysis of Accelerated Destructive Degradation Test Data")
    (description
     "Accelerated destructive degradation tests (ADDT) are often used to collect
necessary data for assessing the long-term properties of polymeric materials.
Based on the collected data, a thermal index (TI) is estimated.  The TI can be
useful for material rating and comparison.  This package implements the
traditional method based on the least-squares method, the parametric method
based on maximum likelihood estimation, and the semiparametric method based on
spline methods, and the corresponding methods for estimating TI for polymeric
materials.  The traditional approach is a two-step approach that is currently
used in industrial standards, while the parametric method is widely used in the
statistical literature.  The semiparametric method is newly developed.  Both the
parametric and semiparametric approaches allow one to do statistical inference
such as quantifying uncertainties in estimation, hypothesis testing, and
predictions.  Publicly available datasets are provided illustrations.  More
details can be found in Jin et al. (2017).")
    (license license:gpl2)))

(define-public r-addscales
  (package
    (name "r-addscales")
    (version "1.0-1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "addScales" version))
              (sha256
               (base32
                "1bw4ljyyswdhqyir9i6lj0mg9lm6ry4zpqp2h6w2bpk37rvs1w38"))))
    (properties `((upstream-name . "addScales")))
    (build-system r-build-system)
    (propagated-inputs (list r-lattice))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=addScales")
    (synopsis
     "Adds Labeled Center Line and Scale Lines/Regions to Trellis Plots")
    (description
     "Modifies trellis objects by adding horizontal and/or vertical reference lines or
shaded regions that provide visual scaling information.  This is mostly useful
in multi-panel plots that use the relation = free option in their scales
argument list.")
    (license license:expat)))

(define-public r-addreg
  (package
    (name "r-addreg")
    (version "3.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "addreg" version))
              (sha256
               (base32
                "13bwmgxylwi02g60j1rr51cr5jvvkl2nvf2lnnhnq46fhvs2ma7s"))))
    (properties `((upstream-name . "addreg")))
    (build-system r-build-system)
    (propagated-inputs (list r-turboem r-glm2 r-combinat))
    (home-page "https://github.com/mdonoghoe/addreg")
    (synopsis "Additive Regression for Discrete Data")
    (description
     "This package provides methods for fitting identity-link GLMs and GAMs to
discrete data, using EM-type algorithms with more stable convergence properties
than standard methods.")
    (license license:gpl2+)))

(define-public r-additivedea
  (package
    (name "r-additivedea")
    (version "1.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "additiveDEA" version))
              (sha256
               (base32
                "15nxpdybsda6yhjk23bpafr8v1zdx8332pcxf26k795q3ypjpiy2"))))
    (properties `((upstream-name . "additiveDEA")))
    (build-system r-build-system)
    (propagated-inputs (list r-lpsolveapi r-benchmarking))
    (home-page "https://www.r-project.org")
    (synopsis "Additive Data Envelopment Analysis Models")
    (description
     "This package provides functions for calculating efficiency with two types of
additive Data Envelopment Analysis models: (i) Generalized Efficiency Measures:
unweighted additive model (Cooper et al., 2007 <doi:10.1007/978-0-387-45283-8>),
Range Adjusted Measure (Cooper et al., 1999, <doi:10.1023/A:1007701304281>),
Bounded Adjusted Measure (Cooper et al., 2011 <doi:10.1007/s11123-010-0190-2>),
Measure of Inefficiency Proportions (Cooper et al., 1999
<doi:10.1023/A:1007701304281>), and the Lovell-Pastor Measure (Lovell and
Pastor, 1995 <doi:10.1016/0167-6377(95)00044-5>); and (ii) the Slacks-Based
Measure (Tone, 2001 <doi:10.1016/S0377-2217(99)00407-5>).  The functions provide
several options: (i) constant and variable returns to scale; (ii) fixed
(non-controllable) inputs and/or outputs; (iii) bounding the slacks so that
unrealistically large slack values are avoided; and (iv) calculating the
efficiency of specific Decision-Making Units (DMUs), rather than of the whole
sample.  Package additiveDEA also provides a function for reducing computation
time when datasets are large.")
    (license license:gpl2)))

(define-public r-additive
  (package
    (name "r-additive")
    (version "0.0.5")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "additive" version))
              (sha256
               (base32
                "1i9837wlz89bl4890735xrb2qi1yaijx8iybr20ky4q9swq3zg7d"))))
    (properties `((upstream-name . "additive")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble
                             r-rlang
                             r-purrr
                             r-parsnip
                             r-mgcv
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://hsbadr.github.io/additive/")
    (synopsis "Bindings for Additive TidyModels")
    (description
     "Fit Generalized Additive Models (GAM) using mgcv with parsnip'/'tidymodels via
additive <doi:10.5281/zenodo.6654298>.  tidymodels is a collection of packages
for machine learning; see Kuhn and Wickham (2020) <https://www.tidymodels.org>).
 The technical details of mgcv are described in Wood (2017)
<doi:10.1201/9781315370279>.")
    (license license:expat)))

(define-public r-addinsoutline
  (package
    (name "r-addinsoutline")
    (version "0.1.6")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "addinsOutline" version))
              (sha256
               (base32
                "125qfqbpv5xflw8qlyh8m3iyd6biyp3arls3z7y8bqkbghifl730"))))
    (properties `((upstream-name . "addinsOutline")))
    (build-system r-build-system)
    (propagated-inputs (list r-yaml
                             r-tibble
                             r-stringr
                             r-shinyfiles
                             r-shiny
                             r-rstudioapi
                             r-rmarkdown
                             r-miniui
                             r-fs
                             r-dt
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/calote/addinsOutline")
    (synopsis
     "'RStudio' Addins for Show Outline of a R Markdown/'LaTeX' Project")
    (description
     "RStudio allows to show and navigate for the outline of a R Markdown file, but
not for R Markdown projects with multiple files.  For this reason, I have
developed several RStudio addins capable of show project outline.  Each addin is
specialized in showing projects of different types: R Markdown project, bookdown
package project and LaTeX project.  There is a configuration file that allows
you to customize additional searches.")
    (license license:gpl3)))

(define-public r-addinslist
  (package
    (name "r-addinslist")
    (version "0.4.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "addinslist" version))
              (sha256
               (base32
                "0dg91lcb2xgsg6sim9fi9m2p203g2dp5bm5q7k0hy084057c22a5"))))
    (properties `((upstream-name . "addinslist")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml2
                             r-shinyjs
                             r-shiny
                             r-rvest
                             r-rmarkdown
                             r-remotes
                             r-rappdirs
                             r-miniui
                             r-dt
                             r-curl))
    (home-page "https://github.com/daattali/addinslist")
    (synopsis "Discover and Install Useful RStudio Addins")
    (description
     "Browse through a continuously updated list of existing RStudio addins and
install/uninstall their corresponding packages.")
    (license license:expat)))

(define-public r-addinsjoaomelo
  (package
    (name "r-addinsjoaomelo")
    (version "0.1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "addinsJoaoMelo" version))
              (sha256
               (base32
                "1slx9vfcpb468asvgcj0vh7djc5rndzdpcp96qmnis77fx67xj5s"))))
    (properties `((upstream-name . "addinsJoaoMelo")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr r-rstudioapi r-purrr r-dplyr))
    (home-page "https://cran.r-project.org/package=addinsJoaoMelo")
    (synopsis "Addins Made of Joao Melo")
    (description
     "Provide addins for RStudio'.  It currently contains 3 addins.  The first to add
a shortcut for the double pipe.  The second is to add a shortcut for the same
operator.  And the third to simplify the creation of vectors from texts pasted
from the computer transfer area.")
    (license license:cc0)))

(define-public r-addhazard
  (package
    (name "r-addhazard")
    (version "1.1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "addhazard" version))
              (sha256
               (base32
                "0hk7br52wjmq605xgslv8lspr35aqpdgkiz2yljz31khy3y3vi8c"))))
    (properties `((upstream-name . "addhazard")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival r-rootsolve r-ahaz))
    (home-page "https://cran.r-project.org/package=addhazard")
    (synopsis "Fit Additive Hazards Models for Survival Analysis")
    (description
     "This package contains tools to fit the additive hazards model to data from a
cohort, random sampling, two-phase Bernoulli sampling and two-phase finite
population sampling, as well as calibration tool to incorporate phase I
auxiliary information into the two-phase data model fitting.  This package
provides regression parameter estimates and their model-based and robust
standard errors.  It also offers tools to make prediction of individual specific
hazards.")
    (license license:gpl2)))

(define-public r-addhaz
  (package
    (name "r-addhaz")
    (version "0.5")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "addhaz" version))
              (sha256
               (base32
                "1709jq9rp5lhqk0qpk8zkdwzhcv1bcach8mm7yiz7hzcc1mgxb12"))))
    (properties `((upstream-name . "addhaz")))
    (build-system r-build-system)
    (propagated-inputs (list r-matrix r-mass r-boot))
    (home-page "https://cran.r-project.org/package=addhaz")
    (synopsis "Binomial and Multinomial Additive Hazard Models")
    (description
     "This package provides functions to fit the binomial and multinomial additive
hazard models and to estimate the contribution of diseases/conditions to the
disability prevalence, as proposed by Nusselder and Looman (2004) and extended
by Yokota et al (2017).")
    (license license:gpl3)))

(define-public r-adct
  (package
    (name "r-adct")
    (version "0.1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ADCT" version))
              (sha256
               (base32
                "1glf83ydx4v3ld8c4gb9h3jk6srd054bis5l8k57p1ba4fnqnnpp"))))
    (properties `((upstream-name . "ADCT")))
    (build-system r-build-system)
    (propagated-inputs (list r-mvtnorm))
    (home-page "https://cran.r-project.org/package=ADCT")
    (synopsis "Adaptive Design in Clinical Trials")
    (description
     "Existing adaptive design methods in clinical trials.  The package includes
power, stopping boundaries (sample size) calculation functions for two-group
group sequential designs, adaptive design with coprimary endpoints,
biomarker-informed adaptive design, etc.")
    (license license:gpl2+)))

(define-public r-adasampling
  (package
    (name "r-adasampling")
    (version "1.3")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AdaSampling" version))
              (sha256
               (base32
                "1c8dh8lxyb076317n4qk2g3qv5j4mc1dszbh3k1p2b0nxiprqk5i"))))
    (properties `((upstream-name . "AdaSampling")))
    (build-system r-build-system)
    (propagated-inputs (list r-mass r-e1071 r-class r-caret))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/PengyiYang/AdaSampling/")
    (synopsis
     "Adaptive Sampling for Positive Unlabeled and Label Noise Learning")
    (description
     "This package implements the adaptive sampling procedure, a framework for both
positive unlabeled learning and learning with class label noise.  Yang, P.,
Ormerod, J., Liu, W., Ma, C., Zomaya, A., Yang, J. (2018)
<doi:10.1109/TCYB.2018.2816984>.")
    (license license:gpl3)))

(define-public r-adapttest
  (package
    (name "r-adapttest")
    (version "1.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "adaptTest" version))
              (sha256
               (base32
                "1qfhb3c64a5pl23vk7z6a3h46yb69cvzp1bpxnpybhxs42s80l5q"))))
    (properties `((upstream-name . "adaptTest")))
    (build-system r-build-system)
    (propagated-inputs (list r-lattice))
    (home-page "https://cran.r-project.org/package=adaptTest")
    (synopsis "Adaptive Two-Stage Tests")
    (description
     "The functions defined in this program serve for implementing adaptive two-stage
tests.  Currently, four tests are included: Bauer and Koehne (1994), Lehmacher
and Wassmer (1999), Vandemeulebroecke (2006), and the horizontal conditional
error function.  User-defined tests can also be implemented.  Reference:
Vandemeulebroecke, An investigation of two-stage tests, Statistica Sinica 2006.")
    (license license:gpl2+)))

(define-public r-adaptsmofmri
  (package
    (name "r-adaptsmofmri")
    (version "1.2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "adaptsmoFMRI" version))
              (sha256
               (base32
                "00npcl2js9vj5r3l66cp5d2l807klia581pig1gsyjjq4rvmfa7v"))))
    (properties `((upstream-name . "adaptsmoFMRI")))
    (build-system r-build-system)
    (propagated-inputs (list r-spatstat-geom
                             r-spatstat
                             r-mvtnorm
                             r-mcmcpack
                             r-matrix
                             r-coda))
    (home-page "https://cran.r-project.org/package=adaptsmoFMRI")
    (synopsis "Adaptive Smoothing of FMRI Data")
    (description
     "Adaptive smoothing functions for estimating the blood oxygenation level
dependent (BOLD) effect by using functional Magnetic Resonance Imaging (fMRI)
data, based on adaptive Gauss Markov random fields, for real as well as
simulated data.  The implemented models make use of efficient Markov Chain Monte
Carlo methods.  Implemented methods are based on the research developed by A.
Brezger, L. Fahrmeir, A. Hennerfeind (2007)
<https://www.jstor.org/stable/4626770>.")
    (license license:gpl2)))

(define-public r-adapts
  (package
    (name "r-adapts")
    (version "1.0.22")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ADAPTS" version))
              (sha256
               (base32
                "0hsignjfq2kbsygpip0fkbncjil8lxryhlhavin09x4xb41kbsva"))))
    (properties `((upstream-name . "ADAPTS")))
    (build-system r-build-system)
    (propagated-inputs (list r-ranger
                             r-quantmod
                             r-preprocesscore
                             r-pheatmap
                             r-pcamethods
                             r-nnls
                             r-missforest
                             r-foreach
                             r-e1071
                             r-doparallel
                             r-comics))
    (home-page "https://cran.r-project.org/package=ADAPTS")
    (synopsis
     "Automated Deconvolution Augmentation of Profiles for Tissue Specific Cells")
    (description
     "Tools to construct (or add to) cell-type signature matrices using flow sorted or
single cell samples and deconvolve bulk gene expression data.  Useful for
assessing the quality of single cell RNAseq experiments, estimating the accuracy
of signature matrices, and determining cell-type spillover.  Please cite:
Danziger SA et al. (2019) ADAPTS: Automated Deconvolution Augmentation of
Profiles for Tissue Specific cells <doi:10.1371/journal.pone.0224693>.")
    (license license:expat)))

(define-public r-adaptr
  (package
    (name "r-adaptr")
    (version "1.1.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "adaptr" version))
              (sha256
               (base32
                "0vq3qavydqyd3vyv6jpgig2qrv8lcnbyy81n3k8sbfcf16p7p0ip"))))
    (properties `((upstream-name . "adaptr")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://incept.dk/")
    (synopsis "Adaptive Trial Simulator")
    (description
     "Package that simulates adaptive clinical trials using adaptive stopping,
adaptive arm dropping, and/or adaptive randomisation.  Developed as part of the
INCEPT (Intensive Care Platform Trial) project (<https://incept.dk/>), which is
primarily supported by a grant from Sygeforsikringen \"danmark\"
(<https://www.sygeforsikring.dk/>).")
    (license license:gpl3+)))

(define-public r-adaptmt
  (package
    (name "r-adaptmt")
    (version "1.0.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "adaptMT" version))
              (sha256
               (base32
                "1yllz1zd4cryf5bj8b2lcrj6zl79yjkllyh9p02ikryy5qmg419b"))))
    (properties `((upstream-name . "adaptMT")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://arxiv.org/abs/1609.06035")
    (synopsis
     "Adaptive P-Value Thresholding for Multiple Hypothesis Testing with Side Information")
    (description
     "Implementation of adaptive p-value thresholding (AdaPT), including both a
framework that allows the user to specify any algorithm to learn local false
discovery rate and a pool of convenient functions that implement specific
algorithms.  See Lei, Lihua and Fithian, William (2016) <arXiv:1609.06035>.")
    (license license:expat)))

(define-public r-adaptmcmc
  (package
    (name "r-adaptmcmc")
    (version "1.4")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "adaptMCMC" version))
              (sha256
               (base32
                "0yydliqhkz1y8lm4sb2biikbk8wmcyfqmamhm059843yk46nr6an"))))
    (properties `((upstream-name . "adaptMCMC")))
    (build-system r-build-system)
    (propagated-inputs (list r-ramcmc r-matrix r-coda))
    (home-page "https://github.com/scheidan/adaptMCMC")
    (synopsis
     "Implementation of a Generic Adaptive Monte Carlo Markov Chain Sampler")
    (description
     "Enables sampling from arbitrary distributions if the log density is known up to
a constant; a common situation in the context of Bayesian inference.  The
implemented sampling algorithm was proposed by Vihola (2012)
<DOI:10.1007/s11222-011-9269-5> and achieves often a high efficiency by tuning
the proposal distributions to a user defined acceptance rate.")
    (license license:gpl2+)))

(define-public r-adaptivpt
  (package
    (name "r-adaptivpt")
    (version "1.0.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "adaptIVPT" version))
              (sha256
               (base32
                "1zjz61zk0q9d1ih3ghzmiz1sxjpdypbx1vl72iw51sqz0nl89n95"))))
    (properties `((upstream-name . "adaptIVPT")))
    (build-system r-build-system)
    (propagated-inputs (list r-rgl r-rcppprogress r-rcpparmadillo r-rcpp))
    (home-page "https://cran.r-project.org/package=adaptIVPT")
    (synopsis "Adaptive Bioequivalence Design for In-Vitro Permeation Tests")
    (description
     "This package contains functions carrying out adaptive procedures using mixed
scaling approach to establish bioequivalence for in-vitro permeation test (IVPT)
data.  Currently, the package provides procedures based on parallel replicate
design and balanced data, according to the U.S. Food and Drug Administration's
\"Draft Guidance on Acyclovir\"
<https:www.accessdata.fda.gov/drugsatfda_docs/psg/Acyclovir_topical cream_RLD
21478_RV12-16.pdf>.  Potvin et al. (2008) <doi:10.1002/pst.294> provides the
basis for our adaptive design (see Method B).  This package reflects the views
of the authors and should not be construed to represent the views or policies of
the U.S. Food and Drug Administration.")
    (license license:gpl3+)))

(define-public r-adaptivetau
  (package
    (name "r-adaptivetau")
    (version "2.2-3")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "adaptivetau" version))
              (sha256
               (base32
                "1jficl4yidix35q8yqs3pcv813wq3pg4hpw4ah4dprvg95bl7wwx"))))
    (properties `((upstream-name . "adaptivetau")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=adaptivetau")
    (synopsis "Tau-Leaping Stochastic Simulation")
    (description
     "This package implements adaptive tau leaping to approximate the trajectory of a
continuous-time stochastic process as described by Cao et al. (2007) The Journal
of Chemical Physics <doi:10.1063/1.2745299> (aka.  the Gillespie stochastic
simulation algorithm).  This package is based upon work supported by NSF
DBI-0906041 and NIH K99-GM104158 to Philip Johnson and NIH R01-AI049334 to
Rustom Antia.")
    (license license:gpl3+)))

(define-public r-adaptivegpca
  (package
    (name "r-adaptivegpca")
    (version "0.1.2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "adaptiveGPCA" version))
              (sha256
               (base32
                "0bb6hw77dfa66b12xyazlp992gwjb1plylixlmq4cv4yjhnl9n5z"))))
    (properties `((upstream-name . "adaptiveGPCA")))
    (build-system r-build-system)
    (propagated-inputs (list r-shiny r-phyloseq r-ggplot2 r-ape))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=adaptiveGPCA")
    (synopsis "Adaptive Generalized PCA")
    (description
     "This package implements adaptive gPCA, as described in: Fukuyama, J. (2017)
<arXiv:1702.00501>.  The package also includes functionality for applying the
method to phyloseq objects so that the method can be easily applied to
microbiome data and a shiny app for interactive visualization.")
    (license license:agpl3)))

(define-public r-adaptgauss
  (package
    (name "r-adaptgauss")
    (version "1.5.6")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AdaptGauss" version))
              (sha256
               (base32
                "076jjnqp4ayq4kh95qns4kfzfvl6mjllhsq6hfp66bww7w976xxh"))))
    (properties `((upstream-name . "AdaptGauss")))
    (build-system r-build-system)
    (propagated-inputs (list r-shiny r-rcpp r-pracma r-datavisualizations))
    (native-inputs (list r-knitr))
    (home-page "https://www.uni-marburg.de/fb12/datenbionik/software-en")
    (synopsis "Gaussian Mixture Models (GMM)")
    (description
     "Multimodal distributions can be modelled as a mixture of components.  The model
is derived using the Pareto Density Estimation (PDE) for an estimation of the
pdf.  PDE has been designed in particular to identify groups/classes in a
dataset.  Precise limits for the classes can be calculated using the theorem of
Bayes.  Verification of the model is possible by QQ plot, Chi-squared test and
Kolmogorov-Smirnov test.  The package is based on the publication of Ultsch, A.,
Thrun, M.C., Hansen-Goos, O., Lotsch, J. (2015) <DOI:10.3390/ijms161025897>.")
    (license license:gpl3)))

(define-public r-adaptdiag
  (package
    (name "r-adaptdiag")
    (version "0.1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "adaptDiag" version))
              (sha256
               (base32
                "02xpphdhvryc06yji89mn7m2djgkpy19ph4sd52rhfsma7xn6hyf"))))
    (properties `((upstream-name . "adaptDiag")))
    (build-system r-build-system)
    (propagated-inputs (list r-pbmcapply r-foreach r-extradistr r-doparallel))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/graemeleehickey/adaptDiag")
    (synopsis "Bayesian Adaptive Designs for Diagnostic Trials")
    (description
     "Simulate clinical trials for diagnostic test devices and evaluate the operating
characteristics under an adaptive design with futility assessment determined via
the posterior predictive probabilities.")
    (license license:gpl3)))

(define-public r-adapt4pv
  (package
    (name "r-adapt4pv")
    (version "0.2-2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "adapt4pv" version))
              (sha256
               (base32
                "08zgzidw0wmpvhzsn4h8yhzgc45zh16grjp4y8mcc9lhk7pikhy5"))))
    (properties `((upstream-name . "adapt4pv")))
    (build-system r-build-system)
    (propagated-inputs (list r-xgboost
                             r-speedglm
                             r-matrix
                             r-glmnet
                             r-foreach
                             r-doparallel))
    (home-page "https://cran.r-project.org/package=adapt4pv")
    (synopsis "Adaptive Approaches for Signal Detection in Pharmacovigilance")
    (description
     "This package provides a collection of several pharmacovigilance signal detection
methods based on adaptive lasso.  Additional lasso-based and propensity
score-based signal detection approaches are also supplied.  See Courtois et al
<doi:10.1186/s12874-021-01450-3>.")
    (license license:gpl2)))

(define-public r-adana
  (package
    (name "r-adana")
    (version "1.1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "adana" version))
              (sha256
               (base32
                "0zi3a17rapc1z074k3yzgjv2b6ba6c9d54b1hm0ivvgfd335981f"))))
    (properties `((upstream-name . "adana")))
    (build-system r-build-system)
    (propagated-inputs (list r-roi-plugin-optimx r-roi r-optimx))
    (home-page "https://cran.r-project.org/package=adana")
    (synopsis
     "Adaptive Nature-Inspired Algorithms for Hybrid Genetic Optimization")
    (description
     "The Genetic Algorithm (GA) is a type of optimization method of Evolutionary
Algorithms.  It uses the biologically inspired operators such as mutation,
crossover, selection and replacement.Because of their global search and
robustness abilities, GAs have been widely utilized in machine learning, expert
systems, data science, engineering, life sciences and many other areas of
research and business.  However, the regular GAs need the techniques to improve
their efficiency in computing time and performance in finding global optimum
using some adaptation and hybridization strategies.  The adaptive GAs (AGA)
increase the convergence speed and success of regular GAs by setting the
parameters crossover and mutation probabilities dynamically.  The hybrid GAs
combine the exploration strength of a stochastic GAs with the exact convergence
ability of any type of deterministic local search algorithms such as
simulated-annealing, in addition to other nature-inspired algorithms such as ant
colony optimization, particle swarm optimization etc.  The package adana
includes a rich working environment with its many functions that make possible
to build and work regular GA, adaptive GA, hybrid GA and hybrid adaptive GA for
any kind of optimization problems.  Cebeci, Z. (2021, ISBN: 9786254397448).")
    (license license:gpl3)))

(define-public r-adahuber
  (package
    (name "r-adahuber")
    (version "1.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "adaHuber" version))
              (sha256
               (base32
                "0giypz04m9anssa2r3hlf95lnj74i3ir48p5j898i2z1gmf8m14w"))))
    (properties `((upstream-name . "adaHuber")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpparmadillo r-rcpp))
    (home-page "https://github.com/XiaoouPan/adaHuber")
    (synopsis "Adaptive Huber Estimation and Regression")
    (description
     "Huber-type estimation for mean, covariance and (regularized) regression.  For
all the methods, the robustification parameter tau is chosen by a tuning-free
principle.")
    (license license:gpl3)))

(define-public r-adace
  (package
    (name "r-adace")
    (version "1.0.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "adace" version))
              (sha256
               (base32
                "1zkvfbvqwxh4k5a0l06khdblm16q7knfcrxfzpmck8053z7kilgr"))))
    (properties `((upstream-name . "adace")))
    (build-system r-build-system)
    (propagated-inputs (list r-reshape2 r-pracma))
    (home-page "https://cran.r-project.org/package=adace")
    (synopsis "Estimator of the Adherer Average Causal Effect")
    (description
     "Estimate the causal treatment effect for subjects that can adhere to one or both
of the treatments.  Given longitudinal data with missing observations,
consistent causal effects are calculated.  Unobserved potential outcomes are
estimated through direct integration as described in: Qu et al., (2019)
<doi:10.1080/19466315.2019.1700157> and Zhang et.  al., (2021)
<doi:10.1080/19466315.2021.1891965>.")
    (license license:gpl3+)))

(define-public r-acwr
  (package
    (name "r-acwr")
    (version "0.1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ACWR" version))
              (sha256
               (base32
                "19q8m5swp7ivrxi8rbkpp37d6fwr35zd8xs4ygpfgd07axc9451s"))))
    (properties `((upstream-name . "ACWR")))
    (build-system r-build-system)
    (propagated-inputs (list r-r2d3))
    (home-page "https://github.com/JorgeDelro/ACWR")
    (synopsis "Acute Chronic Workload Ratio Calculation")
    (description
     "This package provides functions for calculating the acute chronic workload ratio
using three different methods: exponentially weighted moving average (EWMA),
rolling average coupled (RAC) and rolling averaged uncoupled (RAU).  Examples of
this methods can be found in Williams et al. (2017)
<doi:10.1136/bjsports-2016-096589> for EWMA and Windt & Gabbet (2018) for RAC
and RAU <doi: 10.1136/bjsports-2017-098925>.")
    (license license:expat)))

(define-public r-acv
  (package
    (name "r-acv")
    (version "1.0.2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ACV" version))
              (sha256
               (base32
                "078n1if2rkbdhivrzp3lsq35a8awrf5y3s7fi3f5l21a9dmrk4d1"))))
    (properties `((upstream-name . "ACV")))
    (build-system r-build-system)
    (propagated-inputs (list r-matrix r-forecast))
    (home-page "https://cran.r-project.org/package=ACV")
    (synopsis
     "Optimal Out-of-Sample Forecast Evaluation and Testing under Stationarity")
    (description
     "Package ACV (short for Affine Cross-Validation) offers an improved time-series
cross-validation loss estimator which utilizes both in-sample and out-of-sample
forecasting performance via a carefully constructed affine weighting scheme.
Under the assumption of stationarity, the estimator is the best linear unbiased
estimator of the out-of-sample loss.  Besides that, the package also offers
improved versions of Diebold-Mariano and Ibragimov-Muller tests of equal
predictive ability which deliver more power relative to their conventional
counterparts.  For more information, see the accompanying article Stanek (2021)
<doi:10.2139/ssrn.3996166>.")
    (license license:gpl3+)))

(define-public r-acumos
  (package
    (name "r-acumos")
    (version "0.4-4")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "acumos" version))
              (sha256
               (base32
                "15i4xbcdk5vxjrgac32zh4439v0vmabnw3jvsmxiipap5frp7rpi"))))
    (properties `((upstream-name . "acumos")))
    (build-system r-build-system)
    (propagated-inputs (list r-yaml
                             r-rserve
                             r-rprotobuf
                             r-restrserve
                             r-jsonlite
                             r-httr))
    (home-page
     "https://www.acumos.orghttps://gerrit.acumos.org/r/gitweb?p=acumos-r-client.githttps://github.com/acumos/acumos-r-clienthttps://docs.acumos.org/en/latest/submodules/acumos-r-client/docs")
    (synopsis "'Acumos' R Interface")
    (description
     "Create, upload and run Acumos R models.  Acumos (<https://www.acumos.org>) is a
platform and open source framework intended to make it easy to build, share, and
deploy AI apps.  Acumos is part of the LF AI Foundation', an umbrella
organization within The Linux Foundation'.  With this package, user can create a
component, and push it to an Acumos platform.")
    (license license:asl2.0)))

(define-public r-actxps
  (package
    (name "r-actxps")
    (version "0.2.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "actxps" version))
              (sha256
               (base32
                "0yyz70xn8pgcxx85q87i0fz582ia68mymhyxy827z47kwn0s5w18"))))
    (properties `((upstream-name . "actxps")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble
                             r-thematic
                             r-shiny
                             r-scales
                             r-rlang
                             r-recipes
                             r-readr
                             r-rcolorbrewer
                             r-purrr
                             r-paletteer
                             r-lubridate
                             r-gt
                             r-glue
                             r-ggplot2
                             r-generics
                             r-dplyr
                             r-bslib))
    (home-page "https://github.com/mattheaphy/actxps/")
    (synopsis
     "Create Actuarial Experience Studies: Prepare Data, Summarize Results, and Create Reports")
    (description
     "Experience studies are used by actuaries to explore historical experience across
blocks of business and to inform assumption setting activities.  This package
provides functions for preparing data, creating studies, and beginning
assumption development.  Experience study methods, including exposure
calculations, are described in: Atkinson & McGarry (2016) \"Experience Study
Calculations\"
<https://www.soa.org/49378a/globalassets/assets/files/research/experience-study-calculations.pdf>.
 The limited fluctuation credibility method used by the exp_stats() function is
described in: Herzog (1999, ISBN:1-56698-374-6) \"Introduction to Credibility
Theory\".")
    (license license:expat)))

(define-public r-actuaryr
  (package
    (name "r-actuaryr")
    (version "1.1.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "actuaryr" version))
              (sha256
               (base32
                "08dzn565ax2l2hrn2m32k6magjbskybywl0hsgkg11nrjvkznwnx"))))
    (properties `((upstream-name . "actuaryr")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble
                             r-purrr
                             r-magrittr
                             r-lubridate
                             r-dplyr
                             r-crayon))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=actuaryr")
    (synopsis "Develop Actuarial Models")
    (description
     "Actuarial reports are prepared for the last day of a specific period, such as a
month, a quarter or a year.  Actuarial models assume that certain events happen
at the beginning or end of periods.  The package contains functions to easily
refer to the first or last (working) day within a specific period relative to a
base date to facilitate actuarial reporting and to compare results.")
    (license license:expat)))

(define-public r-activitygcmm
  (package
    (name "r-activitygcmm")
    (version "1.1.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "activityGCMM" version))
              (sha256
               (base32
                "0r11z61h8fs5dcm3yfr2njbrbh4pv7xlbqx5zngmrknhv407498z"))))
    (properties `((upstream-name . "activityGCMM")))
    (build-system r-build-system)
    (propagated-inputs (list r-runjags r-overlap r-mclust r-circular))
    (home-page "https://cran.r-project.org/package=activityGCMM")
    (synopsis
     "Circular Mixed Effect Mixture Models of Animal Activity Patterns")
    (description
     "Bayesian parametric generalized circular mixed effect mixture models (GCMMs) for
estimating animal activity patterns from camera trap data and other nested data
structures using JAGS', including automatic Bayesian k-cluster selection and
random circular intercepts for nested data.  The GCMM function automatically
selects the number of components for the mixture model (supporting up to 4
mixture components) based on a Bayesian linear finite normal mixture model and
fits a Bayesian parametric circular mixed effect mixture model with one or two
random effects as random circular intercepts with a a von Mises or wrapped
Cauchy distribution.  Provides graphs of the combined mixture model or separate
mixture components.  Functionality is provided to allow quantitative comparisons
between model parameters.  See Campbell et al. (in press) It's time to expand
our analyses of animal activity; Campbell et al. (in press) Temporal and
microspatial niche partitioning; Campbell et al. (in press) A novel approach to
comparing animal activity patterns.  News, updates, and tutorials will be
available on www.atlasgoldenwolf.org/stats and www.github.com/LizADCampbell .")
    (license license:gpl2+)))

(define-public r-activegp
  (package
    (name "r-activegp")
    (version "1.1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "activegp" version))
              (sha256
               (base32
                "1yfib5q649kag45ryyqsbq9lq9yd74rrjjk65a6c9rkfa4f6w8xv"))))
    (properties `((upstream-name . "activegp")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcppprogress
                             r-rcpparmadillo
                             r-rcpp
                             r-numderiv
                             r-mass
                             r-lhs
                             r-hetgp))
    (home-page "https://cran.r-project.org/package=activegp")
    (synopsis
     "Gaussian Process Based Design and Analysis for the Active Subspace Method")
    (description
     "The active subspace method is a sensitivity analysis technique that finds
important linear combinations of input variables for a simulator.  This package
provides functions allowing estimation of the active subspace without gradient
information using Gaussian processes as well as sequential experimental design
tools to minimize the amount of data required to do so.  Implements Wycoff et
al. (2019) <arXiv:1907.11572>.")
    (license license:bsd-3)))

(define-public r-activatr
  (package
    (name "r-activatr")
    (version "0.1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "activatr" version))
              (sha256
               (base32
                "0c0sn0b5w1k7kgrx8b6vanamlxsr9nqvkwhm0d8imghq8wl90h43"))))
    (properties `((upstream-name . "activatr")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml2
                             r-timetk
                             r-tibble
                             r-rlang
                             r-magrittr
                             r-lubridate
                             r-httr
                             r-glue
                             r-ggmap
                             r-geosphere
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/dschafer/activatr")
    (synopsis "Utilities for Parsing and Plotting Activities")
    (description
     "This contains helpful functions for parsing, managing, plotting, and visualizing
activities, most often from GPX (GPS Exchange Format) files recorded by GPS
devices.  It allows easy parsing of the source files into standard R data
formats, along with functions to compute derived data for the activity, and to
plot the activity in a variety of ways.")
    (license license:expat)))

(define-public r-activanalyzer
  (package
    (name "r-activanalyzer")
    (version "1.0.5")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "activAnalyzer" version))
              (sha256
               (base32
                "1xy98lrlq9rn3v5699jw031wka4fyd7gydgxd5897amnc9in9z31"))))
    (properties `((upstream-name . "activAnalyzer")))
    (build-system r-build-system)
    (propagated-inputs (list r-zoo
                             r-tidyr
                             r-stringr
                             r-shinyjs
                             r-shinyfeedback
                             r-shinydashboardplus
                             r-shinydashboard
                             r-shinycssloaders
                             r-shiny
                             r-rsqlite
                             r-rmarkdown
                             r-reactable
                             r-physicalactivity
                             r-patchwork
                             r-modelr
                             r-magrittr
                             r-lubridate
                             r-hms
                             r-golem
                             r-ggplot2
                             r-forcats
                             r-flextable
                             r-dplyr
                             r-dbplyr))
    (native-inputs (list r-knitr))
    (home-page "https://pydemull.github.io/activAnalyzer/")
    (synopsis
     "'Shiny' App to Analyze Accelerometer-Measured Daily Physical Behavior Data")
    (description
     "This package provides a tool to analyse ActiGraph accelerometer data and to
implement the use of the PROactive Physical Activity in COPD (chronic
obstructive pulmonary disease) instruments.  Once analysis is completed, the app
allows to export results to .csv files and to generate a report of the
measurement.  All the configured inputs relevant for interpreting the results
are recorded in the report.  In addition to the existing R packages that are
fully integrated with the app, the app uses some functions from the
actigraph.sleepr package developed by Petkova (2021)
<https://github.com/dipetkov/actigraph.sleepr/>.")
    (license license:gpl3+)))

(define-public r-actisleep
  (package
    (name "r-actisleep")
    (version "0.2.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ActiSleep" version))
              (sha256
               (base32
                "0nkfddfv0g1bvsg6811lrmy0cx7knmi225snyp22bh9ly9fnlqp8"))))
    (properties `((upstream-name . "ActiSleep")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble
                             r-stringr
                             r-rsqlite
                             r-lubridate
                             r-lazyeval
                             r-dplyr
                             r-dbi
                             r-accelerometry))
    (home-page "https://cran.r-project.org/package=ActiSleep")
    (synopsis "Sleep Duration Estimate Algorithm")
    (description
     "Estimate sleep duration using a Pruned Dynamic Programming (PDP) algorithm that
quickly and efficiently identifies changepoints.  When applied to physical
activity data it can identify transitions from wakefulness to sleep and vice
versa.  Baek, Jonggyu, Banker, Margaret, Jansen, Erica C., She, Xichen,
Peterson, Karen E., Pitchford, E. Andrew, Song, Peter X. K. (2021) \"An Efficient
Segmentation Algorithm to Estimate Sleep Duration from Actigraphy Data\"
<doi:10.1007/s12561-021-09309-3>.")
    (license license:gpl2+)))

(define-public r-actilifecounts
  (package
    (name "r-actilifecounts")
    (version "1.1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "actilifecounts" version))
              (sha256
               (base32
                "1v423byxanbvqk3s76s67r6ivqcg3ld4yddcvf7cmwwlrkd72ck4"))))
    (properties `((upstream-name . "actilifecounts")))
    (build-system r-build-system)
    (propagated-inputs (list r-pracma r-gsignal))
    (home-page "https://cran.r-project.org/package=actilifecounts")
    (synopsis "Generate Activity Counts from Raw Accelerometer Data")
    (description
     "This package provides a tool to obtain activity counts, originally a translation
of the python package agcounts <https://github.com/actigraph/agcounts>.  This
tool allows the processing of data from any accelerometer brand, with a more
flexible approach to handle different sampling frequencies.")
    (license license:lgpl3+)))

(define-public r-actel
  (package
    (name "r-actel")
    (version "1.2.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "actel" version))
              (sha256
               (base32
                "10gv6vc921ma6ckck9807j3j7z0m8kalwv5aj8xg6i2yqnia2zgs"))))
    (properties `((upstream-name . "actel")))
    (build-system r-build-system)
    (propagated-inputs (list r-svglite
                             r-stringr
                             r-stringi
                             r-scales
                             r-rsvg
                             r-rmarkdown
                             r-reshape2
                             r-readr
                             r-knitr
                             r-ggplot2
                             r-fasttime
                             r-diagrammersvg
                             r-diagrammer
                             r-data-table
                             r-circular))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/hugomflavio/actel")
    (synopsis "Acoustic Telemetry Data Analysis")
    (description
     "Designed for studies where animals tagged with acoustic tags are expected to
move through receiver arrays.  This package combines the advantages of automatic
sorting and checking of animal movements with the possibility for user
intervention on tags that deviate from expected behaviour.  The three analysis
functions (explore(), migration() and residency()) allow the users to analyse
their data in a systematic way, making it easy to compare results from different
studies.  CJS calculations are based on Perry et al. (2012)
<https://www.researchgate.net/publication/256443823_Using_mark-recapture_models_to_estimate_survival_from_telemetry_data>.")
    (license license:gpl3)))

(define-public r-actcr
  (package
    (name "r-actcr")
    (version "0.3.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ActCR" version))
              (sha256
               (base32
                "1w3xkq3wanpa2j3rfzzdvad2r3vzzvp76kp56mh2s07p3xql6rv0"))))
    (properties `((upstream-name . "ActCR")))
    (build-system r-build-system)
    (propagated-inputs (list r-zoo r-minpack-lm r-dplyr r-cosinor2 r-cosinor))
    (home-page "https://github.com/junruidi/ActCR")
    (synopsis "Extract Circadian Rhythms Metrics from Actigraphy Data")
    (description
     "Circadian rhythms are rhythms that oscillate about every 24 h, which has been
observed in multiple physiological processes including core body temperature,
hormone secretion, heart rate, blood pressure, and many others.  Measuring
circadian rhythm with wearables is based on a principle that there is increased
movement during wake periods and reduced movement during sleep periods, and has
been shown to be reliable and valid.  This package can be used to extract
nonparametric circadian metrics like intradaily variability (IV), interdaily
stability (IS), and relative amplitude (RA); and parametric cosinor model and
extended cosinor model coefficient.  Details can be found in Junrui Di et al
(2019) <doi:10.1007/s12561-019-09236-4>.")
    (license license:gpl3)))

(define-public r-act
  (package
    (name "r-act")
    (version "1.1.9")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "act" version))
              (sha256
               (base32
                "094sm7afkjrgyhc1p7wj7akrlm65fxwkljgnlldq0z2bf2df07ab"))))
    (properties `((upstream-name . "act")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml2
                             r-xml
                             r-textutils
                             r-stringr
                             r-stringi
                             r-progress
                             r-openxlsx))
    (native-inputs (list r-knitr))
    (home-page "http://www.oliverehmer.de")
    (synopsis "Aligned Corpus Toolkit")
    (description
     "The Aligned Corpus Toolkit (act) is designed for linguists that work with time
aligned transcription data.  It offers functions to import and export various
annotation file formats ('ELAN .eaf, EXMARaLDA .exb and Praat .TextGrid files),
create print transcripts in the style of conversation analysis, search
transcripts (span searches across multiple annotations, search in normalized
annotations, make concordances etc.), export and re-import search results (.csv
and Excel .xlsx format), create cuts for the search results (print transcripts,
audio/video cuts using FFmpeg and video sub titles in Subrib title .srt format),
modify the data in a corpus (search/replace, delete, filter etc.), interact with
Praat using Praat'-scripts, and exchange data with the rPraat package.  The
package is itself written in R and may be expanded by other users.")
    (license license:gpl3)))

(define-public r-acroname
  (package
    (name "r-acroname")
    (version "0.1.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "acroname" version))
              (sha256
               (base32
                "0fff7z3i8h30v7bsyq240h8ws5ld04n6c5r2iizd2icp8dk9xs9x"))))
    (properties `((upstream-name . "acroname")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr
                             r-readr
                             r-r-utils
                             r-purrr
                             r-magrittr
                             r-hunspell
                             r-dplyr))
    (home-page "https://cran.r-project.org/package=acroname")
    (synopsis "Engine for Acronyms and Initialisms")
    (description
     "This package provides a tool for generating acronyms and initialisms from
arbitrary text input.")
    (license license:gpl3)))

(define-public r-acne
  (package
    (name "r-acne")
    (version "0.8.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ACNE" version))
              (sha256
               (base32
                "0kzapsalzw6jsi990qicp4glijh5ddnfimsg5pidgbwxg4i05grl"))))
    (properties `((upstream-name . "ACNE")))
    (build-system r-build-system)
    (propagated-inputs (list r-r-utils
                             r-r-oo
                             r-r-methodss3
                             r-r-filesets
                             r-matrixstats
                             r-mass
                             r-aroma-core
                             r-aroma-affymetrix))
    (home-page "https://github.com/HenrikBengtsson/ACNE")
    (synopsis
     "Affymetrix SNP Probe-Summarization using Non-Negative Matrix Factorization")
    (description
     "This package provides a summarization method to estimate allele-specific copy
number signals for Affymetrix SNP microarrays using non-negative matrix
factorization (NMF).")
    (license license:lgpl2.1+)))

(define-public r-acled-api
  (package
    (name "r-acled-api")
    (version "1.1.6")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "acled.api" version))
              (sha256
               (base32
                "0mri64ir386rn625i0x0kzlqng102dn338slh5cw6lcaa3hjywdq"))))
    (properties `((upstream-name . "acled.api")))
    (build-system r-build-system)
    (propagated-inputs (list r-jsonlite r-httr))
    (home-page "<https://gitlab.com/chris-dworschak/acled.api>")
    (synopsis "Automated Retrieval of ACLED Conflict Event Data")
    (description
     "Access and manage the application programming interface (API) of the Armed
Conflict Location & Event Data Project (ACLED) at <https://acleddata.com/>.  The
package makes it easy to retrieve a user-defined sample (or all of the available
data) of ACLED, enabling a seamless integration of regular data updates into the
research work flow.  It requires a minimal number of dependencies.  See the
package's README file for a note on replicability when drawing on ACLED data.
When using this package, you acknowledge that you have read ACLED's terms and
conditions of use, and that you agree with their attribution requirements.")
    (license (license:fsdg-compatible "CC BY-NC 4.0"))))

(define-public r-acesimfit
  (package
    (name "r-acesimfit")
    (version "0.0.0.9")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ACEsimFit" version))
              (sha256
               (base32
                "0ifwgpnql14z1qzw8fmllgzl97bwd35f0558ymmcxz1mhgh6cb2v"))))
    (properties `((upstream-name . "ACEsimFit")))
    (build-system r-build-system)
    (propagated-inputs (list r-openmx))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=ACEsimFit")
    (synopsis "ACE Kin Pair Data Simulations and Model Fitting")
    (description
     "This package provides a few functions aim to provide a statistic tool for three
purposes.  First, simulate kin pairs data based on the assumption that every
trait is affected by genetic effects (A), common environmental effects (C) and
unique environmental effects (E).Second, use kin pairs data to fit an ACE model
and get model fit output.Third, calculate power of A estimate given a specific
condition.  For the mechanisms of power calculation, we suggest to check
Visscher(2004)<doi:10.1375/twin.7.5.505>.")
    (license license:expat)))

(define-public r-acesearch
  (package
    (name "r-acesearch")
    (version "1.0.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ACEsearch" version))
              (sha256
               (base32
                "1ssq8avj20dk2mal0j5dvshf7qgk0as90sgl71cn91cq8lbiilpn"))))
    (properties `((upstream-name . "ACEsearch")))
    (build-system r-build-system)
    (propagated-inputs (list r-testthat r-httr))
    (home-page "https://shahlab.stanford.edu/start")
    (synopsis "'ACE' Search Engine API")
    (description
     "ACE (Advanced Cohort Engine) is a powerful tool that allows constructing cohorts
of patients extremely quickly and efficiently.  This package is designed to
interface directly with an instance of ACE search engine and facilitates API
queries and data dumps.  Prerequisite is a good knowledge of the temporal
language to be able to efficiently construct a query.  More information
available at <https://shahlab.stanford.edu/start>.")
    (license license:expat)))

(define-public r-acep
  (package
    (name "r-acep")
    (version "0.0.21")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ACEP" version))
              (sha256
               (base32
                "1c3krdxfpdmpj8z3bwi6gqq621n1hvna593bhcmrzkyv2jkc0k7a"))))
    (properties `((upstream-name . "ACEP")))
    (build-system r-build-system)
    (propagated-inputs (list r-httr))
    (home-page "https://github.com/agusnieto77/ACEP")
    (synopsis "Analisis Computacional de Eventos de Protesta")
    (description
     "La libreria ACEP contiene funciones especificas para desarrollar analisis
computacional de eventos de protesta.  Asimismo, contiene base de datos con
colecciones de notas sobre protestas y diccionarios de palabras conflictivas.
Coleccion de diccionarios que reune diccionarios de diferentes origenes.  The
ACEP library contains specific functions to perform computational analysis of
protest events.  It also contains a database with collections of notes on
protests and dictionaries of conflicting words.  Collection of dictionaries that
brings together dictionaries from different sources.")
    (license license:expat)))

(define-public r-aceeditor
  (package
    (name "r-aceeditor")
    (version "1.0.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "aceEditor" version))
              (sha256
               (base32
                "1qdxs20si1smjn24dlgq46x6qwjdwsa0f5lzh1vrbgv4kk9j1rfb"))))
    (properties `((upstream-name . "aceEditor")))
    (build-system r-build-system)
    (propagated-inputs (list r-rstudioapi r-reactr r-htmlwidgets r-htmltools))
    (home-page "https://github.com/stla/aceEditor")
    (synopsis "The 'Ace' Editor as a HTML Widget")
    (description
     "Wraps the Ace editor in a HTML widget.  The Ace editor has support for many
languages.  It can be opened in the viewer pane of RStudio', and this provides a
second source editor.")
    (license license:gpl3)))

(define-public r-acdcr
  (package
    (name "r-acdcr")
    (version "1.0.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "acdcR" version))
              (sha256
               (base32
                "0mf4fhqym4l8m71wgha1587r7sxnmakq3bds24yr425433biiy25"))))
    (properties `((upstream-name . "acdcR")))
    (build-system r-build-system)
    (propagated-inputs (list r-raster r-data-table))
    (home-page "https://github.com/ysd2004/acdcR")
    (synopsis "Agro-Climatic Data by County")
    (description
     "The functions are designed to calculate the most widely-used county-level
variables in agricultural production or agricultural-climatic and weather
analyses.  To operate some functions in this package needs download of the bulk
PRISM raster.  See the examples, testing versions and more details from:
<https://github.com/ysd2004/acdcR>.")
    (license license:gpl2+)))

(define-public r-acdc
  (package
    (name "r-acdc")
    (version "1.0.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "ACDC" version))
              (sha256
               (base32
                "11nlg6pcmfa8pl1f5fxxcig1z1j74yizllh5y9rcdbdfzcasvnzn"))))
    (properties `((upstream-name . "ACDC")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-tibble
                             r-patchwork
                             r-magrittr
                             r-latex2exp
                             r-ggplot2
                             r-dplyr
                             r-desolve
                             r-colorspace))
    (home-page "https://github.com/afmagee/ACDC")
    (synopsis "Analysis of Congruent Diversification Classes")
    (description
     "Features tools for exploring congruent phylogenetic birth-death models.  It can
construct the pulled speciation- and net-diversification rates from a reference
model.  Given alternative speciation- or extinction rates, it can construct new
models that are congruent with the reference model.  Functionality is included
to sample new rate functions, and to visualize the distribution of one
congruence class.  See also Louca & Pennell (2020)
<doi:10.1038/s41586-020-2176-1>.")
    (license license:gpl3)))

(define-public r-accucor
  (package
    (name "r-accucor")
    (version "0.3.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "accucor" version))
              (sha256
               (base32
                "1byhfh9lskgpi8sx6kb7prh88a2jglrjpq206rmh98hqd3r23n5j"))))
    (properties `((upstream-name . "accucor")))
    (build-system r-build-system)
    (propagated-inputs (list r-writexl
                             r-tibble
                             r-stringr
                             r-rlang
                             r-readxl
                             r-readr
                             r-nnls
                             r-dplyr
                             r-chnosz))
    (home-page "https://github.com/XiaoyangSu/AccuCor")
    (synopsis "Natural Abundance Correction of Mass Spectrometer Data")
    (description
     "An isotope natural abundance correction algorithm that is needed especially for
high resolution mass spectrometers.  Supports correction for 13C, 2H and 15N. Su
X, Lu W and Rabinowitz J (2017) <doi:10.1021/acs.analchem.7b00396>.")
    (license license:expat)))

(define-public r-accrualplot
  (package
    (name "r-accrualplot")
    (version "1.0.7")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "accrualPlot" version))
              (sha256
               (base32
                "1xd855yzr405kl6qqm68zgcj3j112xmpkx0f1z8gd9z7s3sr74h0"))))
    (properties `((upstream-name . "accrualPlot")))
    (build-system r-build-system)
    (propagated-inputs (list r-rlang
                             r-purrr
                             r-magrittr
                             r-lubridate
                             r-ggplot2
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/CTU-Bern/accrualPlot")
    (synopsis "Accrual Plots and Predictions for Clinical Trials")
    (description
     "Tracking accrual in clinical trials is important for trial success.  If accrual
is too slow, the trial will take too long and be too expensive.  If accrual is
much faster than expected, time sensitive tasks such as the writing of
statistical analysis plans might need to be rushed.  accrualPlot provides
functions to aid the tracking of accrual and predict when a trial will reach
it's intended sample size.")
    (license license:expat)))

(define-public r-accessrmd
  (package
    (name "r-accessrmd")
    (version "1.0.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "accessrmd" version))
              (sha256
               (base32
                "1jdbbsi8nzvr8hnrpw5sr8zf55irnwwrnkwx4vd0zx84bxvw3bqy"))))
    (properties `((upstream-name . "accessrmd")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr
                             r-rlist
                             r-rcurl
                             r-knitr
                             r-htmltools
                             r-ggplot2))
    (home-page "https://cran.r-project.org/package=accessrmd")
    (synopsis "Improving the Accessibility of 'rmarkdown' Documents")
    (description
     "This package provides a simple method to improve the accessibility of rmarkdown
documents.  The package provides functions for creating or modifying rmarkdown
documents, resolving known errors and alerts that result in accessibility issues
for screen reader users.")
    (license license:expat)))

(define-public r-accessibility
  (package
    (name "r-accessibility")
    (version "1.0.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "accessibility" version))
              (sha256
               (base32
                "1773h1hhq4h4gp6jkbg92ikppw8lnqhv4wlkncg6gr62nid0l3ik"))))
    (properties `((upstream-name . "accessibility")))
    (build-system r-build-system)
    (propagated-inputs (list r-rdpack r-data-table r-checkmate))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/ipeaGIT/accessibility")
    (synopsis "Transport Accessibility Measures")
    (description
     "This package provides a set of fast and convenient functions to calculate
multiple transport accessibility measures.  Given a pre-computed travel cost
matrix and a land use dataset (containing the location of jobs, healthcare and
population, for example), the package allows one to calculate active and passive
accessibility levels using multiple accessibility measures, such as: cumulative
opportunities (using either travel cost cutoffs or intervals), minimum travel
cost to closest N number of activities, gravity-based (with different decay
functions) and different floating catchment area methods.")
    (license license:expat)))

(define-public r-acca
  (package
    (name "r-acca")
    (version "0.2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "acca" version))
              (sha256
               (base32
                "0h9dyzd1pbr4rvxqz69vlfmbibcd1n72qqgjvci7fdjjvfq2mc9p"))))
    (properties `((upstream-name . "acca")))
    (build-system r-build-system)
    (propagated-inputs (list r-plyr r-ggplot2))
    (home-page "https://cran.r-project.org/package=acca")
    (synopsis "Canonical Correlation Analysis with Inferential Guaranties")
    (description
     "It performs Canonical Correlation Analysis and provides inferential guaranties
on the correlation components.  The p-values are computed following the
resampling method developed in Winkler, A. M., Renaud, O., Smith, S. M., &
Nichols, T. E. (2020).  Permutation inference for canonical correlation
analysis.  NeuroImage, <doi:10.1016/j.neuroimage.2020.117065>.  Furthermore, it
provides plotting tools to visualize the results.")
    (license license:gpl2+)))

(define-public r-academictwitter
  (package
    (name "r-academictwitter")
    (version "0.3.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "academictwitteR" version))
              (sha256
               (base32
                "055n0y8g2ibai5zyvw9cqbi0l1zi792cgf65jhy6mrf7j6lgrzhw"))))
    (properties `((upstream-name . "academictwitteR")))
    (build-system r-build-system)
    (propagated-inputs (list r-usethis
                             r-tidyselect
                             r-tidyr
                             r-tibble
                             r-rlang
                             r-purrr
                             r-magrittr
                             r-lubridate
                             r-jsonlite
                             r-httr
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/cjbarrie/academictwitteR")
    (synopsis
     "Access the Twitter Academic Research Product Track V2 API Endpoint")
    (description
     "Package to query the Twitter Academic Research Product Track, providing access
to full-archive search and other v2 API endpoints.  Functions are written with
academic research in mind.  They provide flexibility in how the user wishes to
store collected data, and encourage regular storage of data to mitigate loss
when collecting large volumes of tweets.  They also provide workarounds to
manage and reshape the format in which data is provided on the client side.")
    (license license:expat)))

(define-public r-abstr
  (package
    (name "r-abstr")
    (version "0.4.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "abstr" version))
              (sha256
               (base32
                "0ykds1l7bi0h06fjp0d6xshl8ar05n7ccmjbl7hz02l2v7ncfa6v"))))
    (properties `((upstream-name . "abstr")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-tibble
                             r-sf
                             r-od
                             r-magrittr
                             r-lwgeom
                             r-jsonlite))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/a-b-street/abstr")
    (synopsis
     "R Interface to the A/B Street Transport System Simulation Software")
    (description
     "This package provides functions to convert origin-destination data, represented
as straight desire lines in the sf Simple Features class system, into JSON files
that can be directly imported into A/B Street <https://www.abstreet.org>, a free
and open source tool for simulating urban transport systems and scenarios of
change <doi:10.1007/s10109-020-00342-2>.")
    (license (license:fsdg-compatible "Apache License (>= 2)"))))

(define-public r-abmr
  (package
    (name "r-abmr")
    (version "1.0.6")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "abmR" version))
              (sha256
               (base32
                "12j6l0fsr2qpm6rvmvakvayy5qn0gi01sxpk72jijymn9czsgv8j"))))
    (properties `((upstream-name . "abmR")))
    (build-system r-build-system)
    (propagated-inputs (list r-tmap
                             r-table1
                             r-swfscmisc
                             r-sp
                             r-sf
                             r-rnaturalearthdata
                             r-rnaturalearth
                             r-rgeos
                             r-rgdal
                             r-raster
                             r-purrr
                             r-kableextra
                             r-gtsummary
                             r-gstat
                             r-googledrive
                             r-ggplot2
                             r-geosphere))
    (home-page "https://cran.r-project.org/package=abmR")
    (synopsis "Agent-Based Models in R")
    (description
     "Supplies tools for running agent-based models (ABM) in R, as discussed in
Gochanour et al. (2021) <doi:10.1101/2021.09.15.460374> The package contains two
movement functions, each of which is based on the Ornstein-Uhlenbeck (OU) model
(Ornstein & Uhlenbeck, 1930) <doi:10.1103/PhysRev.36.823>.  It also contains
several visualization and data summarization functions to facilitate the
presentation of simulation results.")
    (license license:gpl3+)))

(define-public r-abjdata
  (package
    (name "r-abjdata")
    (version "1.1.2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "abjData" version))
              (sha256
               (base32
                "0q7l9lxm41pjkdv98axx87wcxjxfyccfwi2k1b29g07pfjszs0hv"))))
    (properties `((upstream-name . "abjData")))
    (build-system r-build-system)
    (home-page "https://abjur.github.io/abjData/")
    (synopsis
     "Databases Used Routinely by the Brazilian Jurimetrics Association")
    (description
     "The Brazilian Jurimetrics Association (ABJ in Portuguese, see
<https://abj.org.br/> for more information) is a non-profit organization which
aims to investigate and promote the use of statistics and probability in the
study of Law and its institutions.  This package has a set of datasets commonly
used in our book.")
    (license license:expat)))

(define-public r-abglasso
  (package
    (name "r-abglasso")
    (version "0.1.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "abglasso" version))
              (sha256
               (base32
                "0h8p912l0202wyr5vjsbzw5mr70m56ab39wv833g6c4c3187479y"))))
    (properties `((upstream-name . "abglasso")))
    (build-system r-build-system)
    (propagated-inputs (list r-statmod r-pracma r-mass))
    (home-page "https://cran.r-project.org/package=abglasso")
    (synopsis "Adaptive Bayesian Graphical Lasso")
    (description
     "This package implements a Bayesian adaptive graphical lasso data-augmented block
Gibbs sampler.  The sampler simulates the posterior distribution of precision
matrices of a Gaussian Graphical Model.  This sampler was adapted from the
original MATLAB routine proposed in Wang (2012) <doi:10.1214/12-BA729>.")
    (license license:gpl3)))

(define-public r-abess
  (package
    (name "r-abess")
    (version "0.4.6")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "abess" version))
              (sha256
               (base32
                "08dyhn8a5lnizlyj33i1fr4mh52yzcnla4q9sanfg17705vvjk6m"))))
    (properties `((upstream-name . "abess")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcppeigen r-rcpp r-matrix r-mass))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/abess-team/abess")
    (synopsis "Fast Best Subset Selection")
    (description
     "Extremely efficient toolkit for solving the best subset selection problem
<https://www.jmlr.org/papers/v23/21-1060.html>.  This package is its R
interface.  The package implements and generalizes algorithms designed in
<doi:10.1073/pnas.2014241117> that exploits a novel sequencing-and-splicing
technique to guarantee exact support recovery and globally optimal solution in
polynomial times for linear model.  It also supports best subset selection for
logistic regression, Poisson regression, Cox proportional hazard model, Gamma
regression, multiple-response regression, multinomial logistic regression,
ordinal regression, (sequential) principal component analysis, and robust
principal component analysis.  The other valuable features such as the best
subset of group selection <arXiv:2104.12576> and sure independence screening
<doi:10.1111/j.1467-9868.2008.00674.x> are also provided.")
    (license (list license:gpl3+
                   (license:fsdg-compatible "file://LICENSE")))))

(define-public r-abdiv
  (package
    (name "r-abdiv")
    (version "0.2.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "abdiv" version))
              (sha256
               (base32
                "053l94br8sdy30078ssncq5i5zvdxa3m72ymbwbh0cm3zmsljj29"))))
    (properties `((upstream-name . "abdiv")))
    (build-system r-build-system)
    (propagated-inputs (list r-ape))
    (home-page "https://github.com/kylebittinger/abdiv")
    (synopsis "Alpha and Beta Diversity Measures")
    (description
     "This package provides a collection of measures for measuring ecological
diversity.  Ecological diversity comes in two flavors: alpha diversity measures
the diversity within a single site or sample, and beta diversity measures the
diversity across two sites or samples.  This package overlaps considerably with
other R packages such as vegan', gUniFrac', betapart', and fossil'.  We also
include a wide range of functions that are implemented in software outside the R
ecosystem, such as scipy', Mothur', and scikit-bio'.  The implementations here
are designed to be basic and clear to the reader.")
    (license license:expat)))

(define-public r-abclass
  (package
    (name "r-abclass")
    (version "0.4.0")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "abclass" version))
              (sha256
               (base32
                "1cg8xfzxya585wzk6y2kf4flgjxlspzqqqksbig8nlxmwxxj413p"))))
    (properties `((upstream-name . "abclass")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpparmadillo r-rcpp))
    (home-page "https://wwenjie.org/abclass")
    (synopsis "Angle-Based Large-Margin Classifiers")
    (description
     "Multi-category angle-based large-margin classifiers.  See Zhang and Liu (2014)
<doi:10.1093/biomet/asu017> for details.")
    (license license:gpl3+)))

(define-public r-abbreviate
  (package
    (name "r-abbreviate")
    (version "0.1")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "abbreviate" version))
              (sha256
               (base32
                "1cvjdbi17qz8gr5898zchm5fyz4n51z66lwps25v8a9mhwab8imi"))))
    (properties `((upstream-name . "abbreviate")))
    (build-system r-build-system)
    (home-page "https://github.com/sigbertklinke/abbreviate")
    (synopsis "Readable String Abbreviation")
    (description
     "Strings are abbreviated to at least \"minlength\" characters, such that they
remain unique (if they were).  The abbreviations should be recognisable.")
    (license license:gpl3)))

(define-public r-aattools
  (package
    (name "r-aattools")
    (version "0.0.2")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AATtools" version))
              (sha256
               (base32
                "10adwxyqnbjw2a0pxrp4qbs68fn2bdxwcbaqmvx5xfgrj4skl68z"))))
    (properties `((upstream-name . "AATtools")))
    (build-system r-build-system)
    (propagated-inputs (list r-magrittr r-foreach r-dplyr r-doparallel))
    (home-page "https://cran.r-project.org/package=AATtools")
    (synopsis
     "Reliability and Scoring Routines for the Approach-Avoidance Task")
    (description
     "Compute approach bias scores using different scoring algorithms, compute
bootstrapped and exact split-half reliability estimates, and compute confidence
intervals for individual participant scores.")
    (license license:gpl3)))