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VariableSelection  

Select Variables for Linear Models
View on CRAN: Click here


Download and install VariableSelection package within the R console
Install from CRAN:
install.packages("VariableSelection")

Install from Github:
library("remotes")
install_github("cran/VariableSelection")

Install by package version:
library("remotes")
install_version("VariableSelection", "1.0.0")



Attach the package and use:
library("VariableSelection")
Maintained by
Shuangshuang Xu
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-02-17
Latest Update: 2026-02-17
Description:
Provides variable selection for linear models and generalized linear models using Bayesian information criterion (BIC) and model posterior probability (MPP). Given a set of candidate predictors, it evaluates candidate models and returns model-level summaries (BIC and MPP) and predictor-level posterior inclusion probabilities (PIP). For more details see Xu, S., Ferreira, M. A., & Tegge, A. N. (2025) <doi:10.48550/arXiv.2510.02628>.
How to cite:
Shuangshuang Xu (2026). VariableSelection: Select Variables for Linear Models. R package version 1.0.0, https://cran.r-project.org/web/packages/VariableSelection. Accessed 14 Mar. 2026.
Previous versions and publish date:
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Functions, R codes and Examples using the VariableSelection R package
Full VariableSelection package functions and examples
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