groupRemMap: Regularized Multivariate Regression for Identifying Master Predictors Using the GroupRemMap Penalty
Version 0.1-0

An implementation of the GroupRemMap penalty for fitting regularized multivariate response regression models under the high-dimension-low-sample-size setting. When the predictors naturally fall into groups, the GroupRemMap penalty encourages procedure to select groups of predictors, while control for the overall sparsity of the final model.

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AuthorXianlong Wang <xwan2@fhcrc.org>, Li Qin, Hexin Zhang, Yuzheng Zhang, Li Hsu, Pei Wang <pei.wang@mssm.edu>
Date of publication2015-04-09 01:07:16
MaintainerXianlong Wang <xwan2@fhcrc.org>
LicenseGPL (>= 2)
Version0.1-0
Package repositoryView on CRAN
InstallationInstall the latest version of this package by entering the following in R:
install.packages("groupRemMap")

Man pages

groupRemMap: A function to fit the regularized multivariate regression...
groupRemMap.cv: Fit GroupRemMap models for a series of tuning parameters and...

Functions

OLS.CV Source code
RSS.CV Source code
group.remmap Man page Source code
group.remmap.cv Man page Source code

Files

src
src/groupremmap.c
NAMESPACE
R
R/groupRemMap.CV.R
R/groupRemMap.R
MD5
DESCRIPTION
man
man/groupRemMap.cv.Rd
man/groupRemMap.Rd
groupRemMap documentation built on May 19, 2017, 8:11 p.m.