Package: ProSGPV 1.0.1

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>.

Authors:Yi Zuo [aut, cre], Thomas Stewart [aut], Jeffrey Blume [aut]

ProSGPV_1.0.1.tar.gz
ProSGPV_1.0.1.zip(r-4.5)ProSGPV_1.0.1.zip(r-4.4)ProSGPV_1.0.1.zip(r-4.3)
ProSGPV_1.0.1.tgz(r-4.5-any)ProSGPV_1.0.1.tgz(r-4.4-any)ProSGPV_1.0.1.tgz(r-4.3-any)
ProSGPV_1.0.1.tar.gz(r-4.5-noble)ProSGPV_1.0.1.tar.gz(r-4.4-noble)
ProSGPV_1.0.1.tgz(r-4.4-emscripten)ProSGPV_1.0.1.tgz(r-4.3-emscripten)
ProSGPV.pdf |ProSGPV.html✨
ProSGPV/json (API)
NEWS

# Install 'ProSGPV' in R:
install.packages('ProSGPV', repos = c('https://zuoyi93.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/zuoyi93/prosgpv/issues

Datasets:

On CRAN:

Conda:

penalized-regression

4.70 score 5 stars 9 scripts 173 downloads 2 exports 15 dependencies

Last updated 4 years agofrom:d07b8f77d2. Checks:9 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 26 2025
R-4.5-winOKMar 26 2025
R-4.5-macOKMar 26 2025
R-4.5-linuxOKMar 26 2025
R-4.4-winOKMar 26 2025
R-4.4-macOKMar 26 2025
R-4.4-linuxOKMar 26 2025
R-4.3-winOKMar 26 2025
R-4.3-macOKMar 26 2025

Exports:gen.sim.datapro.sgpv

Dependencies:brglm2codetoolsenrichwithforeachglmnetiteratorslatticeMASSMatrixnnetnumDerivRcppRcppEigenshapesurvival

ProSGPV in GLM and Cox models

Rendered fromglm-cox-vignette.Rmdusingknitr::rmarkdownon Mar 26 2025.

Last update: 2021-08-24
Started: 2021-04-22

ProSGPV in linear regression

Rendered fromlinear-vignette.Rmdusingknitr::rmarkdownon Mar 26 2025.

Last update: 2021-08-24
Started: 2021-03-28