pcLasso: Principal Components Lasso

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' <doi:10.48550/arXiv.1810.04651>.

Version: 1.2
Imports: svd
Suggests: knitr, rmarkdown
Published: 2020-09-03
DOI: 10.32614/CRAN.package.pcLasso
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
Materials: README
CRAN checks: pcLasso results


Reference manual: pcLasso.pdf
Vignettes: Introduction to pcLasso


Package source: pcLasso_1.2.tar.gz
Windows binaries: r-devel: pcLasso_1.2.zip, r-release: pcLasso_1.2.zip, r-oldrel: pcLasso_1.2.zip
macOS binaries: r-release (arm64): pcLasso_1.2.tgz, r-oldrel (arm64): pcLasso_1.2.tgz, r-release (x86_64): pcLasso_1.2.tgz, r-oldrel (x86_64): pcLasso_1.2.tgz
Old sources: pcLasso archive


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