bigstep: Stepwise Selection for Large Data Sets
Selecting linear and generalized linear models for large data sets using modified stepwise procedure and modern selection criteria (like modifications of Bayesian Information Criterion). Selection can be performed on data which exceed RAM capacity. Bogdan et al., (2004) <doi:10.1534/genetics.103.021683>.
| Version: | 1.1.2 |
| Depends: | R (≥ 3.5.0) |
| Imports: | bigmemory,magrittr,matrixStats,R.utils,RcppEigen,speedglm, stats, utils |
| Suggests: | devtools,knitr,rmarkdown,testthat |
| Published: | 2025-03-10 |
| DOI: | 10.32614/CRAN.package.bigstep |
| Author: | Piotr Szulc [aut, cre] |
| Maintainer: | Piotr Szulc <piotr.michal.szulc at gmail.com> |
| BugReports: | https://github.com/pmszulc/bigstep/issues |
| License: | GPL-3 |
| URL: | https://github.com/pmszulc/bigstep |
| NeedsCompilation: | no |
| Materials: | README,NEWS |
| CRAN checks: | bigstep results |
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