Package: uniLasso
Type: Package
Title: Univariate-Guided Sparse Regression
Version: 2.11
Date: 2026-01-13
Authors@R: c(
	   person("Trevor", "Hastie",role=c("aut", "cre"), email = "hastie@stanford.edu"),
	   person("Rob", "Tibshirani", role=c("aut")),
	   person("Sourav","Chatterjee",role=c("aut"))
	     )
Depends: glmnet, stats, R (>= 3.6.0)
Imports: methods, utils, MASS
Suggests: testthat
Description: 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.
Encoding: UTF-8
License: GPL-2
NeedsCompilation: no
RoxygenNote: 7.3.2
Packaged: 2026-01-22 00:40:40 UTC; hastie
Author: Trevor Hastie [aut, cre],
  Rob Tibshirani [aut],
  Sourav Chatterjee [aut]
Maintainer: Trevor Hastie <hastie@stanford.edu>
Repository: CRAN
Date/Publication: 2026-01-26 17:00:02 UTC
Built: R 4.6.0; ; 2026-04-26 10:58:53 UTC; unix
