SignifReg: Consistent Significance Controlled Variable Selection in Generalized Linear Regression

Provides significance controlled variable selection algorithms with different directions (forward, backward, stepwise) based on diverse criteria (AIC, BIC, adjusted r-square, PRESS, or p-value). The algorithm selects a final model with only significant variables defined as those with significant p-values after multiple testing correction such as Bonferroni, False Discovery Rate, etc. See Zambom and Kim (2018) <doi:10.1002/sta4.210>.

Version: 4.3
Imports: car
Published: 2022-03-22
DOI: 10.32614/CRAN.package.SignifReg
Author: Jongwook Kim, Adriano Zanin Zambom
Maintainer: Adriano Zanin Zambom <adriano.zambom at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
CRAN checks: SignifReg results


Reference manual: SignifReg.pdf


Package source: SignifReg_4.3.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): SignifReg_4.3.tgz, r-oldrel (arm64): SignifReg_4.3.tgz, r-release (x86_64): SignifReg_4.3.tgz, r-oldrel (x86_64): SignifReg_4.3.tgz
Old sources: SignifReg archive


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