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-4.5-noble)BranchGLM_3.0.1.tar.gz(r-4.4-noble)
BranchGLM_3.0.1.tgz(r-4.4-emscripten)BranchGLM_3.0.1.tgz(r-4.3-emscripten)
BranchGLM.pdf |BranchGLM.html✨
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 4 months agofrom:c49426674d. Checks:1 OK, 1 NOTE. Indexed: no.
| Target | Result | Latest binary |
|---|---|---|
| Doc / Vignettes | OK | Jan 27 2025 |
| R-4.5-linux-x86_64 | NOTE | Jan 27 2025 |
Exports:AUCBranchGLMBranchGLM.fitCindexfit.BranchGLMVSMultipleROCCurvesplotCIROCTableVariableImportanceVariableImportance.bootVariableSelection
Dependencies:BHRcppRcppArmadillo
BranchGLM Vignette
Rendered fromBranchGLM-Vignette.Rmdusingknitr::rmarkdownon Jan 27 2025.Last update: 2024-06-12
Started: 2022-05-19
Variable Importance Vignette
Rendered fromVariableImportance-Vignette.Rmdusingknitr::rmarkdownon Jan 27 2025.Last update: 2024-08-22
Started: 2024-08-22
VariableSelection Vignette
Rendered fromVariableSelection-Vignette.Rmdusingknitr::rmarkdownon Jan 27 2025.Last update: 2024-08-22
Started: 2022-10-31
