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.

Version: 4.2
Imports: car
Published: 2021-09-23
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

Downloads:

Reference manual: SignifReg.pdf
Package source: SignifReg_4.2.tar.gz
Windows binaries: r-devel: SignifReg_4.2.zip, r-release: SignifReg_4.2.zip, r-oldrel: SignifReg_4.2.zip
macOS binaries: r-release (arm64): SignifReg_4.1.tgz, r-release (x86_64): SignifReg_4.2.tgz, r-oldrel: SignifReg_4.2.tgz
Old sources: SignifReg archive

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