A method for fitting the entire regularization path of the principal components lasso for linear and logistic regression models. The algorithm uses cyclic coordinate descent in a path-wise fashion. See URL below for more information on the algorithm. See Tay, K., Friedman, J. ,Tibshirani, R., (2014) 'Principal component-guided sparse regression' <arXiv:1810.04651>.
| Version: | 1.0 |
| Imports: | svd |
| Suggests: | knitr, rmarkdown |
| Published: | 2019-01-11 |
| Author: | Jerome Friedman, Kenneth Tay, Robert Tibshirani |
| Maintainer: | Rob Tibshirani <tibs at stanford.edu> |
| License: | GPL-3 |
| URL: | https://arxiv.org/abs/1810.04651 |
| NeedsCompilation: | yes |
| CRAN checks: | pcLasso results |
| Reference manual: | pcLasso.pdf |
| Vignettes: |
Introduction to pcLasso |
| Package source: | pcLasso_1.0.tar.gz |
| Windows binaries: | r-devel: pcLasso_1.0.zip, r-release: pcLasso_1.0.zip, r-oldrel: pcLasso_1.0.zip |
| OS X binaries: | r-release: pcLasso_1.0.tgz, r-oldrel: not available |
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