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: 2.1.6
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: 2024-06-11
DOI: 10.32614/CRAN.package.BranchGLM
Author: Jacob Seedorff [aut, cre]
Maintainer: Jacob Seedorff <jacob-seedorff at>
License: Apache License (≥ 2)
NeedsCompilation: yes
CRAN checks: BranchGLM results


Reference manual: BranchGLM.pdf
Vignettes: BranchGLM Vignette
VariableSelection Vignette


Package source: BranchGLM_2.1.6.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): BranchGLM_2.1.6.tgz, r-oldrel (arm64): BranchGLM_2.1.6.tgz, r-release (x86_64): BranchGLM_2.1.6.tgz, r-oldrel (x86_64): BranchGLM_2.1.6.tgz
Old sources: BranchGLM archive


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