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
Author:	Jongwook Kim, Adriano Zanin Zambom
Maintainer:	Adriano Zanin Zambom <adriano.zambom at csun.edu>
License:	GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation:	no
CRAN checks:	SignifReg results

Documentation:

Reference manual:

SignifReg.pdf

Downloads:

Package source:	SignifReg_4.3.tar.gz
Windows binaries:	r-devel: SignifReg_4.3.zip, r-release: SignifReg_4.3.zip, r-oldrel: SignifReg_4.3.zip
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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