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. 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

Downloads:

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 El Capitan binaries: r-release: bigstep_0.7.4.tgz
OS X Mavericks binaries: r-oldrel: bigstep_0.7.4.tgz
Old sources: bigstep archive

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