OHPL-package {OHPL} | R Documentation |
OHPL: Ordered Homogeneity Pursuit Lasso for Group Variable Selection
Description
Ordered homogeneity pursuit lasso (OHPL) algorithm for group variable selection proposed in Lin et al. (2017) doi:10.1016/j.chemolab.2017.07.004. 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.
Author(s)
Maintainer: Nan Xiao me@nanx.me (ORCID)
Authors:
You-Wu Lin lyw015813@126.com
See Also
Useful links:
Report bugs at https://github.com/nanxstats/OHPL/issues
[Package OHPL version 1.4.1 Index]