StabilizedRegression: Stabilizing Regression and Variable Selection

Contains an implementation of 'StabilizedRegression', a regression framework for heterogeneous data introduced in Pfister et al. (2021) <doi:10.48550/arXiv.1911.01850>. The procedure uses averaging to estimate a regression of a set of predictors X on a response variable Y by enforcing stability with respect to a given environment variable. The resulting regression leads to a variable selection procedure which allows to distinguish between stable and unstable predictors. The package further implements a visualization technique which illustrates the trade-off between stability and predictiveness of individual predictors.

Version: 1.1
Depends: R (≥ 3.5)
Imports: MASS, R6, glmnet, corpcor, ggplot2, ggrepel
Published: 2022-06-30
DOI: 10.32614/CRAN.package.StabilizedRegression
Author: Niklas Pfister [aut, cre], Evan Williams [ctb]
Maintainer: Niklas Pfister <np at>
License: GPL-3
NeedsCompilation: no
CRAN checks: StabilizedRegression results


Reference manual: StabilizedRegression.pdf


Package source: StabilizedRegression_1.1.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): StabilizedRegression_1.1.tgz, r-oldrel (arm64): StabilizedRegression_1.1.tgz, r-release (x86_64): StabilizedRegression_1.1.tgz, r-oldrel (x86_64): StabilizedRegression_1.1.tgz
Old sources: StabilizedRegression archive


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