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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>.

Versions across snapshots

VersionRepositoryFileSize
1.0.0 rolling linux/jammy R-4.5 VariableSelection_1.0.0.tar.gz 109.9 KiB
1.0.0 rolling linux/noble R-4.5 VariableSelection_1.0.0.tar.gz 109.8 KiB
1.0.0 rolling source/ R- VariableSelection_1.0.0.tar.gz 74.1 KiB
1.0.0 latest linux/jammy R-4.5 VariableSelection_1.0.0.tar.gz 109.9 KiB
1.0.0 latest linux/noble R-4.5 VariableSelection_1.0.0.tar.gz 109.8 KiB
1.0.0 latest source/ R- VariableSelection_1.0.0.tar.gz 74.1 KiB
1.0.0 2026-04-26 source/ R- VariableSelection_1.0.0.tar.gz 74.1 KiB
1.0.0 2026-04-23 source/ R- VariableSelection_1.0.0.tar.gz 74.1 KiB
1.0.0 2026-04-09 windows/windows R-4.5 VariableSelection_1.0.0.zip 114.7 KiB

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