regnet: Network-Based Regularization for Generalized Linear Models

Network-based regularization has achieved success in variable selections for high-dimensional biological data, due to its ability to incorporate the correlations among genomic features. This package provides procedures for fitting network-based regularization, minimax concave penalty (MCP) and lasso penalty for generalized linear models. This first version, regnet0.1.1, focuses on binary outcomes. Functions for continuous, survival outcomes and other regularization methods will be included in the forthcoming upgraded version.

Version: 0.1.1
Depends: R (≥ 3.1.0)
Imports: glmnet, stats
Published: 2017-05-23
Author: Jie Ren, Luann C. Jung, Yinhao Du, Cen Wu, Yu Jiang, Junhao Liu
Maintainer: Jie Ren <jieren at ksu.edu>
BugReports: https://github.com/jrhub/regnet/issues
License: GPL-2
URL: https://github.com/jrhub/regnet
NeedsCompilation: no
Materials: README
CRAN checks: regnet results

Downloads:

Reference manual: regnet.pdf
Package source: regnet_0.1.1.tar.gz
Windows binaries: r-devel: regnet_0.1.1.zip, r-release: regnet_0.1.1.zip, r-oldrel: regnet_0.1.1.zip
OS X El Capitan binaries: r-release: regnet_0.1.1.tgz
OS X Mavericks binaries: r-oldrel: regnet_0.1.1.tgz
Old sources: regnet archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=regnet to link to this page.