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-4.4-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)
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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'))

Peer review:

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

Datasets:

On CRAN:

penalized-regression

2 exports 5 stars 1.10 score 15 dependencies 9 scripts 204 downloads

Last updated 3 years agofrom:d07b8f77d2. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKAug 28 2024
R-4.5-winOKAug 28 2024
R-4.5-linuxOKAug 28 2024
R-4.4-winOKAug 28 2024
R-4.4-macOKAug 28 2024
R-4.3-winOKAug 28 2024
R-4.3-macOKAug 28 2024

Exports:gen.sim.datapro.sgpv

Dependencies:brglm2codetoolsenrichwithforeachglmnetiteratorslatticeMASSMatrixnnetnumDerivRcppRcppEigenshapesurvival

ProSGPV in GLM and Cox models

Rendered fromglm-cox-vignette.Rmdusingknitr::rmarkdownon Aug 28 2024.

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

ProSGPV in linear regression

Rendered fromlinear-vignette.Rmdusingknitr::rmarkdownon Aug 28 2024.

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