road2stat/OHPL: Ordered Homogeneity Pursuit Lasso for Group Variable Selection
Version 1.3.9001

Ordered homogeneity pursuit lasso (OHPL) algorithm for group variable selection proposed in Lin et al. (2017) . The OHPL method exploits the homogeneity structure in high-dimensional data and enjoys the grouping effect to select groups of important variables automatically. This feature makes it particularly useful for high-dimensional datasets with strongly correlated variables, such as spectroscopic data.

Getting started

Package details

MaintainerNan Xiao <[email protected]>
LicenseGPL-3 | file LICENSE
Version1.3.9001
URL https://ohpl.io https://github.com/road2stat/OHPL
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("road2stat/OHPL")
road2stat/OHPL documentation built on Oct. 6, 2018, 12:10 p.m.