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.

Version: 1.0.0
Depends: R (≥ 3.5.0)
Imports: bigmemory, magrittr, matrixStats, methods, R.utils, RcppEigen, speedglm, stats, utils
Suggests: devtools, knitr, rmarkdown, testthat
Published: 2018-09-12
Author: Piotr Szulc [aut, cre]
Maintainer: Piotr Szulc <piotr.michal.szulc at gmail.com>
BugReports: http://github.com/pmszulc/bigstep/issues
License: GPL-3
URL: http://github.com/pmszulc/bigstep
NeedsCompilation: no
Materials: README
CRAN checks: bigstep results

Downloads:

Reference manual: bigstep.pdf
Vignettes: The stepwise procedure for big data
Package source: bigstep_1.0.0.tar.gz
Windows binaries: r-devel: bigstep_1.0.0.zip, r-release: bigstep_1.0.0.zip, r-oldrel: bigstep_0.7.4.zip
OS X binaries: r-release: bigstep_1.0.0.tgz, r-oldrel: bigstep_0.7.4.tgz
Old sources: bigstep archive

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