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Presubmission of the AICcPermanova R Package #585
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@ropensci-review-bot check package |
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🚀 The following problems were found in your submission template:
👋 |
Checks for AICcPermanova (v0.0.3)git hash: 16c09792
(Checks marked with 👀 may be optionally addressed.) Package License: MIT + file LICENSE 1. Package DependenciesDetails of Package Dependency Usage (click to open)
The table below tallies all function calls to all packages ('ncalls'), both internal (r-base + recommended, along with the package itself), and external (imported and suggested packages). 'NA' values indicate packages to which no identified calls to R functions could be found. Note that these results are generated by an automated code-tagging system which may not be entirely accurate.
Click below for tallies of functions used in each package. Locations of each call within this package may be generated locally by running 's <- pkgstats::pkgstats(<path/to/repo>)', and examining the 'external_calls' table. basec (8), data.frame (7), nrow (7), length (5), list (4), paste (3), try (3), by (2), colSums (1), drop (1), factor (1), for (1), ifelse (1), is.na (1), log (1), tryCatch (1) statscomplete.cases (4), as.formula (3), AIC (2), df (1), dt (1) data.tablerbindlist (6), data.table (3), setDT (1) foreachforeach (6) AICcPermanovaAICc_permanova2 (1), akaike_adjusted_rsq (1), filter_vif (1), fit_models (1), VIF (1) dplyrvars (3), mutate (1) tidyrpivot_longer (2), pivot_wider (2) veganadonis2 (3), vegdist (1) parallelmakeCluster (3) utilsdata (2), combn (1) carvif (2) doParallelregisterDoParallel (2) furrrfuture_map_dfr (2) futurecluster (1), plan (1) stringrstr_replace_all (2) broomtidy (1) 2. Statistical PropertiesThis package features some noteworthy statistical properties which may need to be clarified by a handling editor prior to progressing. Details of statistical properties (click to open)
The package has:
Statistical properties of package structure as distributional percentiles in relation to all current CRAN packages
All parameters are explained as tooltips in the locally-rendered HTML version of this report generated by the The final measure (
2a. Network visualisationClick to see the interactive network visualisation of calls between objects in package 3.
|
id | name | conclusion | sha | run_number | date |
---|---|---|---|---|---|
4671349520 | pages build and deployment | success | bb8202 | 21 | 2023-04-11 |
4671322567 | pkgcheck | success | 16c097 | 7 | 2023-04-11 |
4671322564 | pkgdown | success | 16c097 | 23 | 2023-04-11 |
4671322566 | R-CMD-check | success | 16c097 | 36 | 2023-04-11 |
4671322561 | test-coverage | success | 16c097 | 16 | 2023-04-11 |
3b. goodpractice
results
R CMD check
with rcmdcheck
R CMD check generated the following check_fail:
- no_import_package_as_a_whole
Test coverage with covr
Package coverage: 93.64
Cyclocomplexity with cyclocomp
No functions have cyclocomplexity >= 15
Static code analyses with lintr
lintr found the following 58 potential issues:
message | number of times |
---|---|
Avoid 1:nrow(...) expressions, use seq_len. | 2 |
Avoid library() and require() calls in packages | 4 |
Lines should not be more than 80 characters. | 52 |
4. Other Checks
Details of other checks (click to open)
✖️ The following 2 function names are duplicated in other packages:
-
fit_models
from manymodelr
-
VIF
from DescTools, fmsb, GLMMadaptive, miceFast, multiColl, regclass, semEff
Package Versions
package | version |
---|---|
pkgstats | 0.1.3.4 |
pkgcheck | 0.1.1.20 |
Editor-in-Chief Instructions:
This package is in top shape and may be passed on to a handling editor
Dear @derek-corcoran-barrios, thanks a lot for your pre-submission and for your efforts making the package pass all our checks. I'll see this carefully and come back to you ASAP. |
Thanks a lot Mauro, I hope you find the package useful 😊
Cheers
…On Wed, 12 Apr 2023, 15:47 Mauro Lepore, ***@***.***> wrote:
Dear @derek-corcoran-barrios <https://github.com/derek-corcoran-barrios>,
thanks a lot for your pre-submission and for your efforts making the
package pass all our checks.
I'll see this carefully and come back to you ASAP.
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Sorry for the delay. Answering your questions:
|
1. This sound great to me, just to answer your question most of the
stats except for the AICc is calculated by vegan or CAR, so I guess
workflow automation fits
2. I will do that
How should I proceed from here? Do I make a new issue?
Cheers
Derek
…On Sun, Apr 23, 2023 at 11:13 PM Mauro Lepore ***@***.***> wrote:
Dear @derek-corcoran-barrios <https://github.com/derek-corcoran-barrios>
Sorry for the delay.
Answering your questions:
1.
Does the package do statistics itself of rather wrap other packages
that do the stats? If it doesn't do stats itself then the standard
(non-stats) category "workflow automation" seems like a good fit.
2.
In the submission template I see "Although not required, we strongly
recommend having a full manuscript prepared when you submit here." Because
it's not required, I think it's OK for you to check that box, maybe with a
comment on when you think it'll be ready?
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Great. Yes, please go ahead and open a new issue -- this time as a full submission (not pre-submission). We'll continue the conversation there. I'll close this pre-submission now. |
Thanks I will do that
Cheers
…On Mon, Apr 24, 2023 at 12:14 PM Mauro Lepore ***@***.***> wrote:
Great.
Yes, please go ahead and open a new issue -- this time as a full
submission (not pre-submission) and remember to fill the space where you're
asked to point to the pre-submission.
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Submitting Author Name: Derek Corcoran
Submitting Author Github Handle: @derek-corcoran-barrios
Repository: https://github.com/Sustainscapes/AICcPerm
Submission type: Pre-submission
Language: en
Scope
Please indicate which category or categories from our package fit policies or statistical package categories this package falls under. (Please check an appropriate box below):
Data Lifecycle Packages
Statistical Packages
Explain how and why the package falls under these categories (briefly, 1-2 sentences). Please note any areas you are unsure of:
The package I build is built to generate a clear workflow for community analysis, specifically for model selection in Permanova, which are a form of regression
If submitting a statistical package, have you already incorporated documentation of standards into your code via the srr package?
Not yet, I am looking into doing it right now, I expect to have it done by the end of this week
Community ecologist in general, I see it as very useful for microbiologists working with dna barcoding taxonomy, botanist that do plots for community analysis, etc.
This package is based on the vegan package, so that package has the analysis made here, however it does not have the model selection capabilities.
Not applicable
There are 2 issues largely for me. I would like to know if the categories I am choosing for the package are the right ones, and the second is that I would like this package to be in either the Methods in ecology and evolution or The Journal of Open Source Software, however when I am asked to check that in the last part of the submission, I am not completely done with the writing of the article, would this be needed to check those boxes?
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