Package: BranchGLM 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'.
Authors:
BranchGLM_3.0.1.tar.gz
BranchGLM_3.0.1.tar.gz(r-4.7-arm64)BranchGLM_3.0.1.tar.gz(r-4.7-x86_64)BranchGLM_3.0.1.tar.gz(r-4.6-arm64)BranchGLM_3.0.1.tar.gz(r-4.6-x86_64)
BranchGLM_3.0.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
BranchGLM/json (API)
| # Install 'BranchGLM' in R: |
| install.packages('BranchGLM', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/jacobseedorff21/branchglm/issues
Last updated from:c49426674d. Checks:6 OK. Indexed: no.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | OK | 213 | ||
| linux-devel-x86_64 | OK | 218 | ||
| source / vignettes | OK | 332 | ||
| linux-release-arm64 | OK | 250 | ||
| linux-release-x86_64 | OK | 236 | ||
| wasm-release | OK | 166 |
Exports:AUCBranchGLMBranchGLM.fitCindexfit.BranchGLMVSMultipleROCCurvesplotCIROCTableVariableImportanceVariableImportance.bootVariableSelection
Dependencies:BHRcppRcppArmadillo
BranchGLM Vignette
Rendered fromBranchGLM-Vignette.Rmdusingknitr::rmarkdownon Jun 01 2026.Last update: 2024-06-12
Started: 2022-05-19
Variable Importance Vignette
Rendered fromVariableImportance-Vignette.Rmdusingknitr::rmarkdownon Jun 01 2026.Last update: 2024-08-22
Started: 2024-08-22
VariableSelection Vignette
Rendered fromVariableSelection-Vignette.Rmdusingknitr::rmarkdownon Jun 01 2026.Last update: 2024-08-22
Started: 2022-10-31