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
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.3.2
Repository: https://trevorhastie.r-universe.dev
Date/Publication: 2026-01-22 00:54:48 UTC
RemoteUrl: https://github.com/trevorhastie/unilasso
RemoteRef: HEAD
RemoteSha: 0f0a44ab4999cd0fb5d9686f125083a25fcf5561
Packaged: 2026-07-03 05:39:31 UTC; root
Author: Trevor Hastie [aut, cre],
  Rob Tibshirani [aut],
  Sourav Chatterjee [aut]
Maintainer: Trevor Hastie <hastie@stanford.edu>