glinternet: Learning Interactions via Hierarchical Group-Lasso Regularization

Group-Lasso INTERaction-NET. Fits linear pairwise-interaction models that satisfy strong hierarchy: if an interaction coefficient is estimated to be nonzero, then its two associated main effects also have nonzero estimated coefficients. Accommodates categorical variables (factors) with arbitrary numbers of levels, continuous variables, and combinations thereof. Implements the machinery described in the paper "Learning interactions via hierarchical group-lasso regularization" (JCGS 2015, Volume 24, Issue 3). Michael Lim & Trevor Hastie (2015) <doi:10.1080/10618600.2014.938812>.

Version: 1.0.5
Published: 2017-07-04
Author: Michael Lim, Trevor Hastie
Maintainer: Michael Lim <michael626 at>
License: GPL-2
NeedsCompilation: yes
CRAN checks: glinternet results


Reference manual: glinternet.pdf
Package source: glinternet_1.0.5.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X El Capitan binaries: r-release: glinternet_1.0.5.tgz
OS X Mavericks binaries: r-oldrel: glinternet_1.0.5.tgz
Old sources: glinternet archive

Reverse dependencies:

Reverse imports: easyml


Please use the canonical form to link to this page.