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>.
| Version: | 1.0.0 |
| 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) |
| Published: | 2026-02-17 |
| DOI: | 10.32614/CRAN.package.VariableSelection (may not be active yet) |
| Author: | Shuangshuang Xu [aut, cre] |
| Maintainer: | Shuangshuang Xu <xshuangshuang at vt.edu> |
| License: | GPL-3 |
| NeedsCompilation: | no |
| Materials: | README |
| CRAN checks: | VariableSelection results |
| Reference manual: | VariableSelection.html , VariableSelection.pdf |
| Vignettes: |
Variable selection for linear models and generalized linear models with BIC-based posterior probability (source, R code) |
| Package source: | VariableSelection_1.0.0.tar.gz |
| Windows binaries: | r-devel: not available, r-release: not available, r-oldrel: not available |
| macOS binaries: | r-release (arm64): not available, r-oldrel (arm64): not available, r-release (x86_64): not available, r-oldrel (x86_64): not available |
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