Stabilizing Regression and Variable Selection R package StabilizedRegression version 1.1 Contains an implementation of 'StabilizedRegression', a regression framework for heterogeneous data introduced in Pfister et al. (2021) <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. Software Depends: R (>= 3.5) Imports: MASS, R6, glmnet, corpcor, ggplot2, ggrepel Niklas Pfister <np@math.ku.dk> Comprehensive R Archive Network (CRAN) Niklas Pfister [aut, cre], Evan Williams [ctb] GPL-3 2022-06-30 application/tgz https://CRAN.R-project.org/package=StabilizedRegression doi:10.32614/CRAN.package.StabilizedRegression