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StabilizedRegression
View on CRAN: Click
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Download and install StabilizedRegression package within the R console
Install from CRAN:
install.packages("StabilizedRegression")
Install from Github:
library("remotes")
install_github("cran/StabilizedRegression") Install by package version:
library("remotes")
install_version("StabilizedRegression", "1.1") Attach the package and use:
library("StabilizedRegression")
Maintained by
Niklas Pfister
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[Scholar Profile | Author Map]
All associated links for this package
First Published: 2020-03-13
Latest Update: 2022-06-30
Description:
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.
How to cite:
Niklas Pfister (2020). StabilizedRegression: Stabilizing Regression and Variable Selection. R package version 1.1, https://cran.r-project.org/web/packages/StabilizedRegression. Accessed 09 Mar. 2026.
Previous versions and publish date:
1.0 (2020-03-13 11:20)
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Other R packages that StabilizedRegression depends,
imports, suggests or enhances
Complete documentation for StabilizedRegression
Functions, R codes and Examples using
the StabilizedRegression R package
Some associated functions: SRanalysis . StabilizedRegression . coef.StabilizedRegression . learn_network . linear_regressor . plot.SRanalysis . predict.StabilizedRegression .
Some associated R codes: SRanalysis.R . StabilizedRegression.R . coef.StabilizedRegression.R . helper_functions.R . learn_network.R . linear_regressor.R . plot.SRanalysis.R . predict.StabilizedRegression.R . Full StabilizedRegression package functions and examples
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