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 under GNU GPL-3), Emmanuel Candes [ctb] (A part of the optimization code was obtained from under GNU GPL-3)
Maintainer: Alexej Gossmann <alexej.go at>
License: GPL-3
NeedsCompilation: no
Materials: README
CRAN checks: grpSLOPE results


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


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