grpSLOPE: Group Sorted L1 Penalized Estimation

Group SLOPE is a penalized linear regression method that is used for adaptive selection of groups of significant predictors in a high-dimensional linear model. The Group SLOPE method can control the (group) false discovery rate at a user-specified level (i.e., control the expected proportion of irrelevant among all selected groups of predictors).

Version: 0.2.1
Imports: SLOPE (≥ 0.1.3)
Suggests: testthat, knitr, rmarkdown, pander
Published: 2016-11-20
Author: Alexej Gossmann [aut, cre], Damian Brzyski [aut], Weijie Su [aut], Malgorzata Bogdan [aut], Ewout van den Berg [ctb] (A part of the optimization code was obtained from http://statweb.stanford.edu/~candes/SortedL1/software.html under GNU GPL-3), Emmanuel Candes [ctb] (A part of the optimization code was obtained from http://statweb.stanford.edu/~candes/SortedL1/software.html under GNU GPL-3)
Maintainer: Alexej Gossmann <alexej.go at googlemail.com>
BugReports: https://github.com/agisga/grpSLOPE/issues
License: GPL-3
URL: https://github.com/agisga/grpSLOPE.git
NeedsCompilation: no
Materials: README
CRAN checks: grpSLOPE results

Downloads:

Reference manual: grpSLOPE.pdf
Vignettes: Basic usage of grpSLOPE
Package source: grpSLOPE_0.2.1.tar.gz
Windows binaries: r-devel: grpSLOPE_0.2.1.zip, r-release: grpSLOPE_0.2.1.zip, r-oldrel: grpSLOPE_0.2.1.zip
OS X Mavericks binaries: r-release: grpSLOPE_0.2.1.tgz, r-oldrel: grpSLOPE_0.2.1.tgz
Old sources: grpSLOPE archive

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