Package: pcLasso 1.2

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' <arxiv:1810.04651>.

Authors:Jerome Friedman, Kenneth Tay, Robert Tibshirani

pcLasso_1.2.tar.gz
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pcLasso_1.2.tgz(r-4.5-x86_64)pcLasso_1.2.tgz(r-4.5-arm64)pcLasso_1.2.tgz(r-4.4-x86_64)pcLasso_1.2.tgz(r-4.4-arm64)pcLasso_1.2.tgz(r-4.3-x86_64)pcLasso_1.2.tgz(r-4.3-arm64)
pcLasso_1.2.tar.gz(r-4.5-noble)pcLasso_1.2.tar.gz(r-4.4-noble)
pcLasso_1.2.tgz(r-4.4-emscripten)pcLasso_1.2.tgz(r-4.3-emscripten)
pcLasso.pdf |pcLasso.html✨
pcLasso/json (API)

# Install 'pcLasso' in R:
install.packages('pcLasso', repos = c('https://tibshirani.r-universe.dev', 'https://cloud.r-project.org'))

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

fortran

3.04 score 22 scripts 183 downloads 4 exports 1 dependencies

Last updated 5 years agofrom:4047b5f890. Checks:11 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKFeb 25 2025
R-4.5-win-x86_64OKFeb 25 2025
R-4.5-mac-x86_64OKFeb 25 2025
R-4.5-mac-aarch64OKFeb 25 2025
R-4.5-linux-x86_64OKFeb 25 2025
R-4.4-win-x86_64OKFeb 25 2025
R-4.4-mac-x86_64OKFeb 25 2025
R-4.4-mac-aarch64OKFeb 25 2025
R-4.3-win-x86_64OKFeb 25 2025
R-4.3-mac-x86_64OKFeb 25 2025
R-4.3-mac-aarch64OKFeb 25 2025

Exports:cv.pcLassopcLassopredict.cv.pcLassopredict.pcLasso

Dependencies:svd

Introduction to pcLasso

Kenneth Tay and Rob Tibshirani

Rendered frompcLasso.Rmdusingknitr::rmarkdownon Feb 25 2025.

Last update: 2019-01-11
Started: 2019-01-11