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