Package: relaxnet
Type: Package
Title: Relaxation of glmnet models (as in relaxed lasso, Meinshausen
        2007)
Version: 0.3-1
Date: 2013-06-15
Author: Stephan Ritter, Alan Hubbard
Maintainer: Stephan Ritter <sritter@berkeley.edu>
Depends: glmnet
Suggests: parallel
Description: Extends the glmnet package with "relaxation", done by
        running glmnet once on the entire predictor matrix, then again
        on each different subset of variables from along the
        regularization path. Relaxation may lead to improved prediction
        accuracy for truly sparse data generating models, as well as
        fewer false positives (i.e. fewer noncontributing predictors in
        the final model). Penalty may be lasso (alpha = 1) or elastic
        net (0 < alpha < 1). For this version, family may be "gaussian"
        or "binomial" only. Takes advantage of fast fortran code from
        the glmnet package.
License: GPL (>= 2)
URL: http://cran.r-project.org/package=relaxnet
Packaged: 2013-06-16 00:01:07 UTC; sritter
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2013-06-17 08:20:12
