ProSGPV: Penalized Regression with Second-Generation P-Values

Implementation of penalized regression with second-generation p-values for variable selection. The one-stage algorithm is extremely fast and the two-stage algorithm has lower parameter estimation bias when data are highly correlated. S3 methods print(), summary(), coef(), and predict() are available for both algorithms, and S3 method plot() is available for the two-stage algorithm. Technical details of the algorithms can be found at <arXiv:2012.07941>.

Version: 0.1.0
Depends: R (≥ 3.5.0), glmnet
Imports: MASS
Published: 2021-01-06
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, https://arxiv.org/abs/2012.07941
NeedsCompilation: no
Materials: README NEWS
CRAN checks: ProSGPV results

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Reference manual: ProSGPV.pdf
Package source: ProSGPV_0.1.0.tar.gz
Windows binaries: r-devel: ProSGPV_0.1.0.zip, r-release: ProSGPV_0.1.0.zip, r-oldrel: ProSGPV_0.1.0.zip
macOS binaries: r-release: ProSGPV_0.1.0.tgz, r-oldrel: ProSGPV_0.1.0.tgz

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