Package: StabilizedRegression 1.1

StabilizedRegression: Stabilizing Regression and Variable Selection

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.

Authors:Niklas Pfister [aut, cre], Evan Williams [ctb]