groupRemMap: Regularized Multivariate Regression for Identifying Master Predictors Using the GroupRemMap Penalty

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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.

Author
Xianlong Wang <xwan2@fhcrc.org>, Li Qin, Hexin Zhang, Yuzheng Zhang, Li Hsu, Pei Wang <pei.wang@mssm.edu>
Date of publication
2015-04-09 01:07:16
Maintainer
Xianlong Wang <xwan2@fhcrc.org>
License
GPL (>= 2)
Version
0.1-0

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Man pages

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

Files in this package

groupRemMap
groupRemMap/src
groupRemMap/src/groupremmap.c
groupRemMap/NAMESPACE
groupRemMap/R
groupRemMap/R/groupRemMap.CV.R
groupRemMap/R/groupRemMap.R
groupRemMap/MD5
groupRemMap/DESCRIPTION
groupRemMap/man
groupRemMap/man/groupRemMap.cv.Rd
groupRemMap/man/groupRemMap.Rd