swaglm: Fast Sparse Wrapper Algorithm for Generalized Linear Models and Testing Procedures for Network of Highly Predictive Variables
Provides a fast implementation of the SWAG algorithm for Generalized Linear Models which allows to perform a meta-learning procedure that combines screening and wrapper methods to find a set of extremely low-dimensional attribute combinations. The package then performs test on the network of selected models to identify the variables that are highly predictive by using entropy-based network measures.
| Version: | 0.0.1 |
| Imports: | Rcpp, fastglm, stats, igraph, gdata, plyr, progress, DescTools, scales, fields |
| LinkingTo: | Rcpp, RcppArmadillo |
| Suggests: | knitr, MASS, rmarkdown |
| Published: | 2025-09-18 |
| DOI: | 10.32614/CRAN.package.swaglm |
| Author: | Lionel Voirol 
[aut, cre],
Yagmur Ozdemir [aut] |
| Maintainer: | Lionel Voirol <lionelvoirol at hotmail.com> |
| License: | AGPL-3 |
| NeedsCompilation: | yes |
| Materials: | README |
| CRAN checks: | swaglm results |
Documentation:
| Reference manual: | swaglm.html , swaglm.pdf |
| Vignettes: |
Run the SWAG algorithm for generalized linear models (source, R code) |
Downloads:
| Package source: | swaglm_0.0.1.tar.gz |
| Windows binaries: | r-devel: swaglm_0.0.1.zip, r-release: swaglm_0.0.1.zip, r-oldrel: swaglm_0.0.1.zip |
| macOS binaries: | r-release (arm64): swaglm_0.0.1.tgz, r-oldrel (arm64): swaglm_0.0.1.tgz, r-release (x86_64): swaglm_0.0.1.tgz, r-oldrel (x86_64): swaglm_0.0.1.tgz |
Linking:
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