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Functions to compute split generalized linear models. The approach fits generalized linear models that split the covariates into groups. The optimal split of the variables into groups and the regularized estimation of the coefficients are performed by minimizing an objective function that encourages sparsity within each group and diversity among them. Example applications can be found in Christidis et al. (2021) <doi:10.48550/arXiv.2102.08591>.
Version: | 1.0.5 |
Imports: | Rcpp (≥ 1.0.3) |
LinkingTo: | Rcpp, RcppArmadillo |
Suggests: | testthat, vctrs, mvnfast |
Published: | 2022-11-22 |
DOI: | 10.32614/CRAN.package.SplitGLM |
Author: | Anthony Christidis [aut, cre], Stefan Van Aelst [aut], Ruben Zamar [aut] |
Maintainer: | Anthony Christidis <anthony.christidis at stat.ubc.ca> |
License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
NeedsCompilation: | yes |
Materials: | README NEWS |
CRAN checks: | SplitGLM results |
Reference manual: | SplitGLM.pdf |
Package source: | SplitGLM_1.0.5.tar.gz |
Windows binaries: | r-devel: SplitGLM_1.0.5.zip, r-release: SplitGLM_1.0.5.zip, r-oldrel: SplitGLM_1.0.5.zip |
macOS binaries: | r-release (arm64): SplitGLM_1.0.5.tgz, r-oldrel (arm64): SplitGLM_1.0.5.tgz, r-release (x86_64): SplitGLM_1.0.5.tgz, r-oldrel (x86_64): SplitGLM_1.0.5.tgz |
Old sources: | SplitGLM archive |
Reverse imports: | stepSplitReg |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.