jrhub/regnet: Network-Based Regularization for Generalized Linear Models
Version 0.2.0

Network-based regularization has achieved success in variable selection for high-dimensional biological data due to its ability to incorporate correlations between genomic features. This package provides procedures for fitting network-based regularization, minimax concave penalty (MCP) and lasso penalty for generalized linear models. This current version, regnet0.2.0, focuses on binary outcomes. Functions for continuous, survival outcomes and other regularization methods will be included in the forthcoming upgraded versions.

Getting started

Package details

AuthorJie Ren, Luann C. Jung, Yinhao Du, Cen Wu, Yu Jiang, Junhao Liu
MaintainerJie Ren <[email protected]>
LicenseGPL-2
Version0.2.0
URL https://github.com/jrhub/regnet
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("devtools")
library(devtools)
install_github("jrhub/regnet")
jrhub/regnet documentation built on Oct. 20, 2017, 1:59 a.m.