Stabilizing Regression and Variable Selection

Contains an implementation of 'StabilizedRegression', a regression framework for heterogeneous data introduced in Pfister et al. (2019) . 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.


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install.packages("StabilizedRegression")

1.0 by Niklas Pfister, 4 months ago


Report a bug at https://github.com/NiklasPfister/StabilizedRegression-R/issues


Browse source code at https://github.com/cran/StabilizedRegression


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


Documentation:   PDF Manual  


GPL-3 license


Imports MASS, R6, glmnet, corpcor, ggplot2, ggrepel


See at CRAN