uniLasso
2.11Univariate-Guided Sparse Regression
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Overview
About
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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Slowest check: 2.2 min · r-devel-linux-x86_64-fedora-clang
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- OK2026-03-1014 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
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Dependencies
Declared dependencies
2 external dependencies (excludes base and recommended)
Depends (3)
R >= 3.6.0glmnetstats
Imports (3)
methodsutilsMASS
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none
Suggests (1)
Enhances (0)
none
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Code & Tests
People & History
People (3)
Maintainer (1)
Author, Maintainer
Authors (3)
Package Timeline
1 release. R releases are shown for context.
- RR 4.6.0 released · 2026-04-24
- 2.11Latest2026-03-10 · current release
- RR 4.5.0 released · 2025-04-11
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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