grpreg: Regularization paths for regression models with grouped
covariates
Efficient algorithms for fitting the regularization path
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.
| Version: |
1.2-1 |
| Depends: |
R (≥ 2.13.0) |
| Published: |
2011-07-06 |
| Author: |
Patrick Breheny |
| Maintainer: |
Patrick Breheny <patrick.breheny at uky.edu> |
| License: |
GPL-2 |
| Citation: |
grpreg citation info |
| CRAN checks: |
grpreg results |
Downloads: