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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.

Versions across snapshots

VersionRepositoryFileSize
1.1 rolling linux/jammy R-4.5 StabilizedRegression_1.1.tar.gz 129.9 KiB
1.1 rolling linux/noble R-4.5 StabilizedRegression_1.1.tar.gz 129.9 KiB
1.1 rolling source/ R- StabilizedRegression_1.1.tar.gz 16.9 KiB
1.1 latest linux/jammy R-4.5 StabilizedRegression_1.1.tar.gz 129.9 KiB
1.1 latest linux/noble R-4.5 StabilizedRegression_1.1.tar.gz 129.9 KiB
1.1 latest source/ R- StabilizedRegression_1.1.tar.gz 16.9 KiB
1.1 2026-04-26 source/ R- StabilizedRegression_1.1.tar.gz 16.9 KiB
1.1 2026-04-23 source/ R- StabilizedRegression_1.1.tar.gz 16.9 KiB
1.1 2026-04-09 windows/windows R-4.5 StabilizedRegression_1.1.zip 133.4 KiB
1.1 2025-04-20 source/ R- StabilizedRegression_1.1.tar.gz 16.9 KiB

Dependencies (latest)

Imports