glmmLasso: Variable Selection for Generalized Linear Mixed Models by L1-Penalized Estimation

A variable selection approach for generalized linear mixed models by L1-penalized estimation is provided.

Version:	1.5.1
Imports:	minqa, Matrix
Published:	2017-05-06
Author:	Andreas Groll
Maintainer:	Andreas Groll <groll at mathematik.uni-muenchen.de>
License:	GPL-2
NeedsCompilation:	no
CRAN checks:	glmmLasso results

Documentation:

Reference manual:

glmmLasso.pdf

Downloads:

Package source:	glmmLasso_1.5.1.tar.gz
Windows binaries:	r-devel: glmmLasso_1.5.1.zip, r-release: glmmLasso_1.5.1.zip, r-oldrel: glmmLasso_1.5.1.zip
macOS binaries:	r-release (arm64): glmmLasso_1.5.1.tgz, r-oldrel (arm64): glmmLasso_1.5.1.tgz, r-release (x86_64): glmmLasso_1.5.1.tgz, r-oldrel (x86_64): glmmLasso_1.5.1.tgz
Old sources:	glmmLasso archive

Reverse dependencies:

Reverse imports:

autoMrP

Linking:

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