STOPES: Selection Threshold Optimized Empirically via Splitting

Implements variable selection procedures for low to moderate size generalized linear regressions models. It includes the STOPES functions for linear regression (Capanu M, Giurcanu M, Begg C, Gonen M, Optimized variable selection via repeated data splitting, Statistics in Medicine, 2020, 19(6):2167-2184) as well as subsampling based optimization methods for generalized linear regression models (Marinela Capanu, Mihai Giurcanu, Colin B Begg, Mithat Gonen, Subsampling based variable selection for generalized linear models).

Version: 0.2
Imports: MASS, cvTools, glmnet, changepoint
Published: 2022-05-27
Author: Marinela Capanu [aut, cre], Mihai Giurcanu [aut, ctb], Colin Begg [aut], Mithat Gonen [aut]
Maintainer: Marinela Capanu <capanum at mskcc.org>
License: GPL-2
NeedsCompilation: no
CRAN checks: STOPES results

Documentation:

Reference manual: STOPES.pdf

Downloads:

Package source: STOPES_0.2.tar.gz
Windows binaries: r-devel: STOPES_0.2.zip, r-release: STOPES_0.1.zip, r-oldrel: STOPES_0.1.zip
macOS binaries: r-release (arm64): STOPES_0.1.tgz, r-oldrel (arm64): STOPES_0.1.tgz, r-release (x86_64): STOPES_0.1.tgz, r-oldrel (x86_64): STOPES_0.1.tgz
Old sources: STOPES archive

Linking:

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