Package: uniLasso 2.11

uniLasso: Univariate-Guided Sparse Regression

Fit a univariate-guided sparse regression (lasso), by a two-stage procedure. The first stage fits p separate univariate models to the response. The second stage gives more weight to the more important univariate features, and preserves their signs. Conveniently, it returns an objects that inherits from class 'glmnet', so that all of the methods for 'glmnet' are available. See Chatterjee, Hastie and Tibshirani (2025) <doi:10.1162/99608f92.c79ff6db> for details.

Authors:Trevor Hastie [aut, cre], Rob Tibshirani [aut], Sourav Chatterjee [aut]

uniLasso_2.11.tar.gz
uniLasso_2.11.zip(r-4.7-any)uniLasso_2.11.zip(r-4.6-any)uniLasso_2.11.zip(r-4.5-any)
uniLasso_2.11.tgz(r-4.6-any)uniLasso_2.11.tgz(r-4.5-any)
uniLasso_2.11.tar.gz(r-4.7-any)uniLasso_2.11.tar.gz(r-4.6-any)
uniLasso_2.11.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
uniLasso/json (API)

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

Bug tracker:https://github.com/trevorhastie/unilasso/issues

On CRAN:

Conda:

5.02 score 25 stars 21 scripts 211 downloads 13 exports 11 dependencies

Last updated from:0f0a44ab49. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK202
source / vignettesOK242
linux-releaseOK199
macos-releaseOK129
macos-oldrelOK106
windows-develOK93
windows-releaseOK95
windows-oldrelOK96
wasm-releaseOK121

Exports:ci.uniRegcv.uniLassocv.uniRegpolish.uniLassoprint.cv.uniRegsimulate_counterexamplesimulate_Gaussiansimulate_twoclasssimulate_uniLassouniCoefuniInfouniLassouniReg

Dependencies:codetoolsforeachglmnetiteratorslatticeMASSMatrixRcppRcppEigenshapesurvival