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VariableSelection: Select Variables for Linear Models
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>.
Getting started
Browse package contents
Package details |
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| Author | Shuangshuang Xu [aut, cre] |
| Maintainer | Shuangshuang Xu <xshuangshuang@vt.edu> |
| License | GPL-3 |
| Version | 1.0.0 |
| Package repository | View on CRAN |
| Installation |
Install the latest version of this package by entering the following in R:
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Try the VariableSelection package in your browser
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