sparsenet: Fit Sparse Linear Regression Models via Nonconvex Optimization

Efficient procedure for fitting regularization paths between L1 and L0, using the MC+ penalty of Zhang, C.H. (2010)<doi:10.1214/09-AOS729>. Implements the methodology described in Mazumder, Friedman and Hastie (2011) <doi:10.1198/jasa.2011.tm09738>. Sparsenet computes the regularization surface over both the family parameter and the tuning parameter by coordinate descent.

Version: 1.6
Depends: Matrix (≥ 1.0-6), shape
Imports: methods
Published: 2024-02-05
DOI: 10.32614/CRAN.package.sparsenet
Author: Rahul Mazumder [aut, cre], Trevor Hastie [aut, cre], Jerome Friedman [aut, cre]
Maintainer: Trevor Hastie <hastie at>
License: GPL-2
NeedsCompilation: yes
Citation: sparsenet citation info
CRAN checks: sparsenet results


Reference manual: sparsenet.pdf


Package source: sparsenet_1.6.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): sparsenet_1.6.tgz, r-oldrel (arm64): sparsenet_1.6.tgz, r-release (x86_64): sparsenet_1.6.tgz, r-oldrel (x86_64): sparsenet_1.6.tgz
Old sources: sparsenet archive

Reverse dependencies:

Reverse imports: cmenet
Reverse suggests: BOSSreg


Please use the canonical form to link to this page.