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. Software Depends: R (>= 2.13.0) Patrick Breheny <patrick.breheny@uky.edu> Patrick Breheny GPL-2 2011-07-06 application/tgz http://CRAN.R-project.org/package=grpreg