relaxo: Relaxed Lasso

Relaxed Lasso is a generalisation of the Lasso shrinkage technique for linear regression. Both variable selection and parameter estimation is achieved by regular Lasso, yet both steps do not necessarily use the same penalty parameter. The results include all standard Lasso solutions but allow often for sparser models while having similar or even slightly better predictive performance if many predictor variables are present. The package depends on the LARS package.

Version: 0.1-2
Depends: lars
Imports: graphics, utils, stats
Published: 2012-06-01
Author: Nicolai Meinshausen
Maintainer: Nicolai Meinshausen <meinshausen at>
License: GPL-2 | GPL-3 [expanded from: GPL]
NeedsCompilation: no
In views: MachineLearning
CRAN checks: relaxo results


Reference manual: relaxo.pdf
Package source: relaxo_0.1-2.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X Snow Leopard binaries: r-release: relaxo_0.1-2.tgz, r-oldrel: relaxo_0.1-2.tgz
OS X Mavericks binaries: r-release: relaxo_0.1-2.tgz
Old sources: relaxo archive

Reverse dependencies:

Reverse suggests: fscaret