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Linear Model with Tree-Based Lasso Regularization for Rare Features

1packages depend
2.5Kdownloads / year
–test coverage
13/13flavors OK

Overview

About

Implementation of an alternating direction method of multipliers algorithm for fitting a linear model with tree-based lasso regularization, which is proposed in Algorithm 1 of Yan and Bien (2020) doi:10.1080/01621459.2020.1796677. The package allows efficient model fitting on the entire 2-dimensional regularization path for large datasets. The complete set of functions also makes the entire process of tuning regularization parameters and visualizing results hassle-free.

Install

Health

CRAN checks
13OK
Slowest check: 3.6 min · r-devel-windows-x86_64
Status changes
  • OK13 OK2026-08-05
  • NOTE12 OK, 1 NOTE2026-08-01
  • OK13 OK2026-05-06
  • ERROR12 OK, 1 ERROR2026-05-05
  • OK14 OK2026-04-22
Show 2 earlier changesHide 2 earlier changes
  • ERROR13 OK, 1 ERROR2026-04-18
  • OK14 OK2026-03-10
Advisories

none known

Documentation

In release 0.1.2
READMEYes · 65 wordsVignettesYes · 1 · dynamicNEWSNoCitation fileNoWebsitenot declared in DESCRIPTION
Help pages
11includes a package overview page
Examples that run
0%7 never run
Exported functions with examples
100%
Documented parameters
96%
Return-value docs
86%
Help pages citing references
36%

Downloads

2.5K
CRAN downloads in the past year
Rank #17,113 · ~7/day · ~212/mo
Daily download trend is not available in this view yet.
30930 days
73790 days
2.5K1 year
Compare downloads with other packages →
Also on339 r2u7 autocran

Repository

11Stars
4Forks
0Open issues
0Open PRs
0Releases
14Commits
2Commit identities
14 commits · Last activity 2022-01-24 · 0% stars, 30d · The default branch showed an older version (0.1.1) than CRAN on 2026-10-18
Responsiveness
How these are sampled
PRs merged (all time)
100%
Median days to close, 50 most recently updated closed issues
not measured
Median days to close, 50 most recently updated closed PRs
0

Stars over time

2023-02-22 · 102026-07-07 · 11
PracticesBeta

3 development-tooling and community-health practices detected across 3 families in the upstream repository

Checks run against github.com/yanxht/rare on 2026-10-18.

Docs source (1)
README.Rmd
CRAN release process (1)
cran-comments.md
Lint, format, editor (1)
RStudio project
How this is detected·Detection ruleset v3 (2026-09-26)

Dependencies

Declared dependencies
7 external dependencies (excludes base and recommended)

Installing rare adds 7 packages (4 with compiled code, 8.2 MB of source tarballs). Heaviest: glmnet 2.7 MB, Rcpp 1.8 MB, RcppEigen 1.7 MB.

Depends (1)
R >= 3.2.1
Imports (3)
LinkingTo (2)
Enhances (0)
none
Reverse dependencies
1direct
0indirect
Imports 1
Depends, Imports or LinkingTo, most downloaded first

Datasets

People & History

People (2)
Author, Maintainer since 0.1.0 (2018)
Releases (3)

Pick two releases to compare their code metrics.

  • R
    R 4.6.0 released · 2026-04-24
  • 0.1.2Latest
    record
    2025-06-16 · current release · diff ↗
  • R
    R 4.5.0 released · 2025-04-11
  • R
    R 4.4.0 released · 2024-04-24
  • R
    R 4.3.0 released · 2023-04-21
  • R
    R 4.2.0 released · 2022-04-22
  • R
    R 4.1.0 released · 2021-05-18
  • R
    R 4.0.0 released · 2020-04-24
  • R
    R 3.6.0 released · 2019-04-26
  • unarchivedReturned to CRAN
    2018-08-03
  • 0.1.1
    record
    2018-08-03 · diff ↗
  • archivedRemoved from CRAN
    2018-05-07
    check problems were not corrected despite reminders Array overruns detected by ASAN
  • R
    R 3.5.0 released · 2018-04-23
  • 0.1.0
    record
    2018-03-22
  • R
    R 3.4.0 released · 2017-04-21

Package metadata

First published
2018-03-22
Total releases
3 / 8 yrs
License
GPL-3 OSI
Minimum R
≥ 3.2.1
Bundled data
8.7 KB / 3 files
Download size
2.1 MB

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("rare")
Yan, X., & Bien, J. (2025). rare: Linear Model with Tree-Based Lasso Regularization for Rare Features (Version 0.1.2) [Computer software]. https://doi.org/10.32614/CRAN.package.rare

This package has no citation file, so citation() returns this entry built from DESCRIPTION.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

APA

Balamuta, J. J. (2026). R Observatory: Metrics for rare version 0.1.2 [Data set]. HJJB, LLC. Data release v2026-10-20. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-20, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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