splitSelect: Best Split Selection Modeling for Low-Dimensional Data

Functions to generate or sample from all possible splits of features or variables into a number of specified groups. Also computes the best split selection estimator (for low-dimensional data) as defined in Christidis, Van Aelst and Zamar (2019) <arXiv:1812.05678>.

Version: 1.0.1
Imports: multicool, glmnet, parallel, doParallel, foreach, caret
Suggests: testthat, mvnfast
Published: 2020-09-01
Author: Anthony Christidis, Stefan Van Aelst, Ruben Zamar
Maintainer: Anthony Christidis <anthony.christidis at stat.ubc.ca>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
Materials: README NEWS
CRAN checks: splitSelect results

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Reference manual: splitSelect.pdf
Package source: splitSelect_1.0.1.tar.gz
Windows binaries: r-devel: splitSelect_1.0.1.zip, r-release: splitSelect_1.0.1.zip, r-oldrel: splitSelect_1.0.1.zip
macOS binaries: r-release: splitSelect_1.0.1.tgz, r-oldrel: splitSelect_1.0.1.tgz
Old sources: splitSelect archive

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