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>
License: GPL-2
NeedsCompilation: no
Materials: README
CRAN checks: regnet results


Reference manual: regnet.pdf
Package source: regnet_0.1.1.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
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


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