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 stats.ox.ac.uk> |
| License: | GPL-2 | GPL-3 [expanded from: GPL] |
| URL: | http://www.stats.ox.ac.uk/~meinshau/ |
| 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: relaxo_0.1-2.zip, r-release: relaxo_0.1-2.zip, r-oldrel: relaxo_0.1-2.zip |
| macOS binaries: | r-release (arm64): relaxo_0.1-2.tgz, r-oldrel (arm64): relaxo_0.1-2.tgz, r-release (x86_64): relaxo_0.1-2.tgz, r-oldrel (x86_64): relaxo_0.1-2.tgz |
| Old sources: | relaxo archive |
| Reverse imports: | CSUV |
| Reverse suggests: | fscaret |
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