version 1.0.1

cran · Jan 25, 2024 · dda6068 · dda6068
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diff --git a/DESCRIPTION b/DESCRIPTION
@@ -7,7 +7,7 @@ Description: A system for combining two diagnostic tests using various approache
               and machine learning algorithms. See 
               the <http://biosoft.erciyes.edu.tr/app/dtComb> website 
               for more information, documentation, and examples.
-Version: 1.0.0
+Version: 1.0.1
 Authors@R: c(person("Serra Ilayda","Yerlitas", role = c("aut", "ctb"),email = "ilaydayerlitas340@gmail.com"),
             person("Serra Bersan","Gengec", role = c("aut", "ctb"),email = "serrabersan@gmail.com"),
             person("Necla","Kochan", role = c("aut", "ctb"),email = "necla.kayaalp@gmail.com"),
@@ -22,9 +22,9 @@ Imports: pROC (>= 1.18.0), caret, epiR, gam, ggplot2, ggpubr, glmnet,
 License: MIT + file LICENSE
 Encoding: UTF-8
 LazyData: true
-RoxygenNote: 7.2.3
+RoxygenNote: 7.3.1
 NeedsCompilation: no
-Packaged: 2023-12-11 21:07:48 UTC; serrailaydayerlitas
+Packaged: 2024-01-23 15:23:06 UTC; serrailaydayerlitas
 Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
 Config/testthat/edition: 3
 VignetteBuilder: knitr
@@ -36,4 +36,4 @@ Author: Serra Ilayda Yerlitas [aut, ctb],
   Gokmen Zararsiz [aut, ctb, cre]
 Maintainer: Gokmen Zararsiz <gokmen.zararsiz@gmail.com>
 Repository: CRAN
-Date/Publication: 2023-12-12 19:00:02 UTC
+Date/Publication: 2024-01-24 16:02:51 UTC
diff --git a/LICENSE b/LICENSE
@@ -1,2 +1,2 @@
-YEAR: 2023
+YEAR: 2024
 COPYRIGHT HOLDER: dtComb authors
diff --git a/MD5 b/MD5
@@ -1,8 +1,8 @@
-257d91a76c92393dabfed15fd965c1ac *DESCRIPTION
-6c0ed5ad4223da2c9d76f39bd5ddd34d *LICENSE
-62697ae45e904370065381da01449f7a *NAMESPACE
+6ed360bc94690ee0ae8cff9db960a3a7 *DESCRIPTION
+7e3f5989e71f0a3698f3002e7159ebed *LICENSE
+a8b18057c669d85b2b2b3cd4802b1dd6 *NAMESPACE
 ca71064c02566607b9a44b99694613e1 *R/data.R
-9f7ffa675295fef965d8fd2bbbc2052b *R/dtComb.R
+5f7cd4c962e982a1c2df9e7d67060544 *R/dtComb.R
 c1844a0395e990f2c2803daed4d61e64 *R/globals.R
 69807733a19b0515a2febdc170ca3429 *R/linComb.R
 c36b8a886140f59bc9c899d205302574 *R/mathComb.R
@@ -20,11 +20,11 @@ d86694958306984e46a0d3053bf860da *README.md
 443219caefd91c87e765f58471eb21c0 *data/exampleData2.rda
 528f5bae4a16f0235d6af1bd46e6ae2d *data/exampleData3.rda
 aaa7d8a1a2814fd808a3f5775b999376 *inst/doc/vignettedtComb.R
-7234c958249fbadc3b1ea8faff5e2416 *inst/doc/vignettedtComb.Rnw
-25e5f404cc80db43cfe6b39941967a00 *inst/doc/vignettedtComb.pdf
+6e886189cb0df8d7087b8741e73542b9 *inst/doc/vignettedtComb.Rnw
+822bcdb7c5448b4f9043100b46f42046 *inst/doc/vignettedtComb.pdf
 7dbffdd9477fea05ef77ded83592ed5f *man/allMethods.Rd
 a4342261ea48290ad70eb3f8750a7059 *man/availableMethods.Rd
-a6767928fd8457d148792c4cbffa43ba *man/dtComb.Rd
+bf63bd722ffd6ccf0c5538a2e7a7208d *man/dtComb.Rd
 0f01346ee89a0f65d4e91df94ebcbe59 *man/exampleData1.Rd
 30bd23a3f76f77b8f1917446473ff43a *man/exampleData2.Rd
 00e670939573d82dfc52cf8bc86cda04 *man/exampleData3.Rd
@@ -46,18 +46,20 @@ e31b9b6a4fff032fedbacbb1884a8781 *man/print_train.Rd
 a044ae282fbdda10e4f88fbcf376c526 *man/std.train.Rd
 893667e253e7767d34bf4a18ab19e466 *man/transform_math.Rd
 031482eb15265c2885cd4cdf976da76f *tests/testthat.R
+00805e7ff12d3a99f2d45d1ec5bb6db7 *tests/testthat/Rplots.pdf
 23d7f29169fdf42bff5341e51e6b2520 *tests/testthat/result_data/mayo.rda
 f2756b14d8f883518ebef75cecb6791d *tests/testthat/result_data/test_linComb.rda
 cc7d121dfb91d955d56e13dda05adc47 *tests/testthat/result_data/test_mathComb.rda
 f8edc0dcb62c3a7586fef0bfe7c852ab *tests/testthat/result_data/test_nonlinComb.rda
 6e04a05bc2372bf78cd1ba1339323780 *tests/testthat/result_data/test_predComb.rda
 c4f7ec0f24b08bd57e962f51b5311447 *tests/testthat/result_data/test_std.test.rda
 b44401cb234475d064949d078415c061 *tests/testthat/result_data/test_std.train.rda
+c6dd5a2909808f3a901cf00cfd8dfff0 *tests/testthat/result_data/wdbc.data.txt
 1b2b7e25d675e8743c91ff6d714234cd *tests/testthat/test-linComb.R
-f6743bf95787ccfef89030ea55c2ebff *tests/testthat/test-mathComb.R
+d86601b71114b361059be7b5990dac42 *tests/testthat/test-mathComb.R
 531bcde330ca32c6dcd70bf5ca231d15 *tests/testthat/test-mlComb.R
 1df8413bf5906006183bcbb5ca916b88 *tests/testthat/test-nonlinComb.R
 c584e5ef5d07a17367b40d9647922025 *tests/testthat/test-predComb.R
 fad180f9527284cafbe0ea112b037a03 *tests/testthat/test-standardize.R
 e9ad92c8ad27596efef608ab9e405471 *vignettes/dtComb.bib
-7234c958249fbadc3b1ea8faff5e2416 *vignettes/vignettedtComb.Rnw
+6e886189cb0df8d7087b8741e73542b9 *vignettes/vignettedtComb.Rnw
diff --git a/NAMESPACE b/NAMESPACE
@@ -1,18 +1,18 @@
-# Generated by roxygen2: do not edit by hand
-
-S3method(predict,dtComb)
-export(availableMethods)
-export(helper_PCL)
-export(helper_PT)
-export(helper_TS)
-export(helper_minimax)
-export(helper_minmax)
-export(linComb)
-export(mathComb)
-export(mlComb)
-export(nonlinComb)
-export(plotComb)
-export(std.train)
-export(transform_math)
-importFrom(pROC,auc)
-importFrom(stats,'predict')
+# Generated by roxygen2: do not edit by hand
+
+S3method(predict,dtComb)
+export(availableMethods)
+export(helper_PCL)
+export(helper_PT)
+export(helper_TS)
+export(helper_minimax)
+export(helper_minmax)
+export(linComb)
+export(mathComb)
+export(mlComb)
+export(nonlinComb)
+export(plotComb)
+export(std.train)
+export(transform_math)
+importFrom(pROC,auc)
+importFrom(stats,'predict')
diff --git a/R/dtComb.R b/R/dtComb.R
@@ -8,4 +8,4 @@
 #'
 #' @docType package
 #' @name dtComb
-NULL
+"_PACKAGE"
diff --git a/inst/doc/vignettedtComb.Rnw b/inst/doc/vignettedtComb.Rnw
@@ -17,33 +17,28 @@
 \usepackage{amsmath}
 \usepackage{amsfonts}
 \usepackage{amssymb}
-\usepackage{Sweave}
 \usepackage[numbers]{natbib}
-\usepackage{nameref} % cross-reference for section names.
+\usepackage{nameref} 
 \usepackage{booktabs}
 \usepackage{caption}
 \RequirePackage{graphicx, fancyvrb, textcomp}
-\usepackage{authblk}  % authors and affiliations
+
+\usepackage{authblk}
 \setcounter{Maxaffil}{0}
 \renewcommand\Affilfont{\itshape\small}
 
-%%% New Commands %%%
 \newcommand{\dtComb}{\textit{dtComb}}
-% \newcommand{\Biocpkg}[1]{\href{https://www.bioconductor.org/packages/release/bioc/html/#1.html}{\texttt{#1}}}
 \newcommand{\CRANpkg}[1]{\href{https://cran.r-project.org/web/packages/#1/index.html}{\texttt{#1}}}
 \newcommand{\Rfunction}[1]{\texttt{#1}}
 \newcommand{\Rcode}[1]{\texttt{#1}}
 \newcommand{\Rclass}[1]{\texttt{#1}}
 \newcommand{\software}[1]{\texttt{#1}}
 
-%%%% Set knitr options %%%%
 <<echo=FALSE>>=
 library(knitr)
 opts_chunk$set(tidy = FALSE, dev = "pdf", message = FALSE, fig.align = "center", cache = FALSE)
 @
 
-%%%% Load required packages %%%%
-
 
 \title{\textbf{dtComb: A Comprehensive R Package for Combining Two Diagnostic Tests}}
 
@@ -71,7 +66,6 @@ opts_chunk$set(tidy = FALSE, dev = "pdf", message = FALSE, fig.align = "center",
 
 \begin{abstract}
 \CRANpkg{dtComb} is a comprehensive R package that combines two different diagnostic tests. Using its extensive collection of 143 combination methods, the \CRANpkg{dtComb} package enables researchers to standardize their data and merge diagnostic tests. Users can load the dataset containing the reference list and the diagnostic tests they intend to utilize. The package includes combination methods grouped into four main categories: linear combination methods (\Rfunction{linComb}), non-linear combination methods (\Rfunction{nonlinComb}), mathematical operators (\Rfunction{mathComb}), and machine-learning algorithms (\Rfunction{mlComb}). The package incorporates eight specific combination methods from the literature within the scope of linear combination methods. Non-linear combination methods encompass statistical approaches like polynomial regression, penalized regression methods, and splines, incorporating the interactions between the diagnostic tests. Mathematical operators involve arithmetic operations and eight \texttt{distance measures} adaptable to various data structures. Finally, machine-learning algorithms include 113 models from the \CRANpkg{caret} package tailored for \CRANpkg{dtComb}'s data structure. The data standardization step includes five different methods: Z-score, T-score, Mean, Deviance, and Range standardization. The \CRANpkg{dtComb} integrates machine-learning approaches, enabling the utilization of preprocessing methods available in the \CRANpkg{caret} package for standardization purposes within the \CRANpkg{dtComb} environment. The \CRANpkg{dtComb} package allows users to fine-tune hyperparameters while building a model. This is accomplished through resampling techniques such as 10-fold cross-validation, bootstrapping, and 10-fold repeated cross-validation. Since machine-learning algorithms are directly adapted from the \CRANpkg{caret} package, all resampling methods available in the \CRANpkg{caret} package are applicable within the \CRANpkg{dtComb} environment. Following the model building, the \Rfunction{predict} function predicts the class labels and returns the combination scores of new observations from the test set. The \CRANpkg{dtComb} package is designed to be user-friendly and easy to use and is currently the most comprehensive package developed to combine diagnostic tests in the literature. This vignette was created to guide researchers on how to use this package. 
-%%%%%%%%%
 \vspace{1em}
 \noindent\textbf{dtComb version:} \Sexpr{packageDescription("dtComb")$Version}
 \end{abstract}

diff --git a/inst/doc/vignettedtComb.pdf b/inst/doc/vignettedtComb.pdf
diff --git a/man/dtComb.Rd b/man/dtComb.Rd
diff --git a/tests/testthat/Rplots.pdf b/tests/testthat/Rplots.pdf