Efficient Best Subset Selection for GLMs via Branch and Bound Algorithms [R package BranchGLM version 3.0.1]

Jacob Seedorff

BranchGLM: Efficient Best Subset Selection for GLMs via Branch and Bound Algorithms

Performs efficient and scalable glm best subset selection using a novel implementation of a branch and bound algorithm. To speed up the model fitting process, a range of optimization methods are implemented in 'RcppArmadillo'. Parallel computation is available using 'OpenMP'.

Version: 3.0.1

Depends: R (≥ 3.3.0)

Imports: Rcpp (≥ 1.0.7), methods, stats, graphics

LinkingTo: Rcpp, RcppArmadillo, BH

Suggests: knitr, rmarkdown, testthat (≥ 3.0.0)

Published: 2024年09月28日

DOI: 10.32614/CRAN.package.BranchGLM

Author: Jacob Seedorff [aut, cre]

Maintainer: Jacob Seedorff <jacob-seedorff at uiowa.edu>

BugReports: https://github.com/JacobSeedorff21/BranchGLM/issues

License: Apache License (≥ 2)

URL: https://github.com/JacobSeedorff21/BranchGLM