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ProSGPV: Penalized Regression with Second-Generation P-Values

Implementation of penalized regression with second-generation p-values for variable selection. The algorithm can handle linear regression, GLM, and Cox regression. S3 methods print(), summary(), coef(), predict(), and plot() are available for the algorithm. Technical details can be found at Zuo et al. (2021) <doi:10.1080/00031305.2021.1946150>.

Version: 1.0.0
Depends: R (≥ 3.5.0), glmnet, brglm2
Imports: MASS, survival
Suggests: rmarkdown, knitr
Published: 2021-08-06
DOI: 10.32614/CRAN.package.ProSGPV
Author: Yi Zuo ORCID iD [aut, cre], Thomas Stewart [aut], Jeffrey Blume [aut]
Maintainer: Yi Zuo <yi.zuo at vanderbilt.edu>
BugReports: https://github.com/zuoyi93/ProSGPV/issues
License: GPL-3
URL: https://github.com/zuoyi93/ProSGPV
NeedsCompilation: no
Materials: README NEWS
CRAN checks: ProSGPV results

Documentation:

Reference manual: ProSGPV.pdf
Vignettes: ProSGPV in GLM and Cox models
ProSGPV in linear regression

Downloads:

Package source: ProSGPV_1.0.0.tar.gz
Windows binaries: r-devel: ProSGPV_1.0.0.zip, r-release: ProSGPV_1.0.0.zip, r-oldrel: ProSGPV_1.0.0.zip
macOS binaries: r-release (arm64): ProSGPV_1.0.0.tgz, r-oldrel (arm64): ProSGPV_1.0.0.tgz, r-release (x86_64): ProSGPV_1.0.0.tgz, r-oldrel (x86_64): ProSGPV_1.0.0.tgz
Old sources: ProSGPV archive

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.