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. Special selection strategy is available, faster than classical stepwise procedure.
| Version: | 0.7.4 |
| Depends: | R (≥ 3.2.2) |
| Imports: | stats, methods, utils, RcppEigen, speedglm, bigmemory, R.utils, matrixStats |
| Suggests: | testthat, devtools |
| Published: | 2017-04-05 |
| Author: | Piotr Szulc |
| Maintainer: | Piotr Szulc <piotr.michal.szulc at gmail.com> |
| License: | GPL-3 |
| NeedsCompilation: | no |
| CRAN checks: | bigstep results |
| Reference manual: | bigstep.pdf |
| Package source: | bigstep_0.7.4.tar.gz |
| Windows binaries: | r-devel: bigstep_0.7.4.zip, r-release: bigstep_0.7.4.zip, r-oldrel: bigstep_0.7.4.zip |
| OS X binaries: | r-release: bigstep_0.7.4.tgz, r-oldrel: bigstep_0.7.4.tgz |
| Old sources: | bigstep archive |
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