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uniLasso

2.11

Univariate-Guided Sparse Regression

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test coverage
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Overview

About
Maintained by Trevor HastieFirst published 2026-01-261 releasesCRAN page ↗

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.

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Health

CRAN checks
13OK
Slowest check: 2.2 min · r-devel-linux-x86_64-fedora-clang
Code health
None
Tests · ratio 0.00
not tracked
Coverage
100%
Documentation · exports
5
Dependencies · direct
Check history
  • OK2026-03-10
    14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE

Documentation

Documentation
READMEYes · 82 wordsVignettesNopkgdown siteNoNEWSNoCode of conductNoContributing guideNo
Examples that run
100%
Documented parameters
85%
Return-value docs
100%
References docs
0%

Downloads

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Dependencies

Declared dependencies
2 external dependencies (excludes base and recommended)
Depends (3)
R >= 3.6.0glmnetstats
Imports (3)
methodsutilsMASS
LinkingTo (0)
none
Suggests (1)
Enhances (0)
none
Reverse dependencies
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Code & Tests

People & History

People (3)
Maintainer (1)
Author, Maintainer
Authors (3)
Author, Maintainer
Package Timeline

1 release. R releases are shown for context.

  • R
    R 4.6.0 released · 2026-04-24
  • 2.11Latest
    2026-03-10 · current release
  • R
    R 4.5.0 released · 2025-04-11

Package metadata

First published
2026-01-26
Total releases
1 / 1 yrs
License
GPL-2 OSI
Minimum R
≥ 3.6.0
Download size
22 KB
Installed size
not tracked yet
With dependencies
not tracked yet
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