grpreg-package {grpreg} | R Documentation |
This package fits regularization paths for linear or logistic regression models penalized by the group lasso, group bridge, or group MCP methods. The algorithm is based on the idea of a locally approximated coordinate descent, and is stable and very fast.
Package: | grpreg |
Type: | Package |
Version: | 1.1 |
Date: | 2009-11-12 |
License: | GPL-2 |
Accepts a design matrix X
, a vector of responses y
, and
covariate grouping group
, and produces the regularization path
over a grid of values for the tuning parameter lambda
. Also
provides methods for selecting the optimal point along the path using a
variety of information criteria and for plotting the paths.
Patrick Breheny <patrick.breheny@uky.edu>
Breheny, P. and Huang, J. (2009) Penalized methods for bi-level variable selection. Statistics and its interface, 2: 369–380.
data(birthwt.grpreg) X <- as.matrix(birthwt.grpreg[,-1:-2]) y <- birthwt.grpreg$bwt group <- c(1,1,1,2,2,2,3,3,4,5,5,6,7,8,8,8) fit <- grpreg(X,y,group,penalty="gMCP") plot(fit) select(fit,X,y)