Select Variables for Linear Models R package VariableSelection version 1.0.0 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>. Software Depends: R (>= 3.5.0) Imports: stats (>= 4.2.2), GA (>= 3.2.3), memoise (>= 2.0.1) Suggests: knitr, rmarkdown, testthat (>= 3.0.0) Shuangshuang Xu <xshuangshuang@vt.edu> Comprehensive R Archive Network (CRAN) Shuangshuang Xu [aut, cre] GPL-3 2026-02-17 application/tgz https://CRAN.R-project.org/package=VariableSelection doi:10.32614/CRAN.package.VariableSelection