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Home Page: https://ejikeugba.github.io/serp
Smooth Effects on Response Penalty for CLM
Home Page: https://ejikeugba.github.io/serp
https://docs.github.com/en/communities is a good guide to follow. Ends up being added in the markdown files for the repo, and then also shows up as part of the GitHub pages pkgdown site.
I see your package has a good code coverage but upon closer inspection of what is tested, most of the tests related to errors. It would be good to have some regression tests, where you compare the numerical output of some functions to what is known to be correct (e.g., from earlier versions). This prevents the introduction of a bug that would return incorrect values in the future.
Snapshot testing in testthat provides a convenient way to address this issue: https://testthat.r-lib.org/reference/expect_snapshot.html
This issue is part of openjournals/joss-reviews#3705.
I didn't notice this package had a pkgdown website until it was mentioned in openjournals/joss-reviews#3705. I think it would be helpful to add here in the usual places where people look:
Additionally, you should add it in your _pkgdown.yml
file to enable cross-linking from other pkgdown websites, as explained in the downlit README
.
I see that you are using cat()
whenever you want to communicate with the user. It is considered better practice to use message()
instead so that it is directed to the correct output (stderr
instead of stdout
) and it can be silenced by the user via suppressMessages()
.
See this great stack overflow answer for a longer explanation: https://stackoverflow.com/a/36700294/4439357
This issue is part of openjournals/joss-reviews#3705.
@ejikeugba - I suggest editing the README.md and add a short section at the top on dependencies. Yes, CRAN handles it, but it's good to warn the user of incoming forced-installs of packages.
As noted in the whedon check, you need DOIs for a few of the refs.
MISSING DOIs
10.2307/2288515 may be a valid DOI for title: Advanced Econometrics: A Bridge to the Literature
10.1007/bf02985802 may be a valid DOI for title: The Elements of Statistical Learning: Data Mining, Inference and Prediction
10.18637/jss.v099.i06 may be a valid DOI for title: Regularized ordinal regression and the ordinalNet R package
Here are some suggestions to improve the manuscript.
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