pbreheny/grpreg: Regularization Paths for Regression Models with Grouped Covariates

Efficient algorithms for fitting the regularization path of linear regression, GLM, and Cox regression models with grouped penalties. This includes group selection methods such as group lasso, group MCP, and group SCAD as well as bi-level selection methods such as the group exponential lasso, the composite MCP, and the group bridge.

Getting started

Package details

Maintainer
LicenseGPL-3
Version3.2-0
URL http://pbreheny.github.io/grpreg https://github.com/pbreheny/grpreg
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("pbreheny/grpreg")
pbreheny/grpreg documentation built on Sept. 30, 2018, 11:01 a.m.