OPTS: Optimization via Subsampling (OPTS)

Subsampling based variable selection for low dimensional generalized linear models. The methods repeatedly subsample the data minimizing an information criterion (AIC/BIC) over a sequence of nested models for each subsample. Marinela Capanu, Mihai Giurcanu, Colin B Begg, Mithat Gonen, Subsampling based variable selection for generalized linear models.

Version: 0.1
Imports: MASS, cvTools, changepoint
Published: 2022-05-25
Author: Mihai Giurcanu [aut, cre], Marinela Capanu [aut, ctb], Colin Begg [aut], Mithat Gonen [aut]
Maintainer: Mihai Giurcanu <giurcanu at uchicago.edu>
License: GPL-2
NeedsCompilation: no
CRAN checks: OPTS results

Documentation:

Reference manual: OPTS.pdf

Downloads:

Package source: OPTS_0.1.tar.gz
Windows binaries: r-devel: OPTS_0.1.zip, r-release: OPTS_0.1.zip, r-oldrel: OPTS_0.1.zip
macOS binaries: r-release (arm64): OPTS_0.1.tgz, r-oldrel (arm64): OPTS_0.1.tgz, r-release (x86_64): OPTS_0.1.tgz

Linking:

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