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sparseR

0.3.2Package record

Variable Selection under Ranked Sparsity Principles for Interactions and Polynomials

0packages depend
3.3Kdownloads / year
87.9%test coverage
13/13flavors OK

Overview

About

An implementation of ranked sparsity methods, including penalized regression methods such as the sparsity-ranked lasso, its non-convex alternatives, and elastic net, as well as the sparsity-ranked Bayesian Information Criterion. As described in Peterson and Cavanaugh (2022) doi:10.1007/s10182-021-00431-7, ranked sparsity is a philosophy with methods primarily useful for variable selection in the presence of prior informational asymmetry, which occurs in the context of trying to perform variable selection in the presence of interactions and/or polynomials. Ultimately, this package attempts to facilitate dealing with cumbersome interactions and polynomials while not avoiding them entirely. Typically, models selected under ranked sparsity principles will also be more transparent, having fewer falsely selected interactions and polynomials than other methods.

Changes in 0.3.2
  • Fixed issue in CRAN CMD CHECK on Linux caused by setting an attribute on a built-in

From NEWS.md in the release

Install

Health

CRAN checks
13OK
Slowest check: 4.9 min · r-oldrel-windows-x86_64
Status changes
  • OK13 OK2026-09-18
  • ERROR12 OK, 1 ERROR2026-09-12
  • OK13 OK2026-08-04
  • NOTE12 OK, 1 NOTE2026-08-01
  • OK13 OK2026-06-09
Show 2 earlier changesHide 2 earlier changes
  • ERROR12 OK, 1 ERROR2026-06-08
  • OK14 OK2026-03-10
Advisories

none known

Documentation

In release 0.3.2
READMEYes · 189 wordsVignettesYes · 1 · dynamicNEWSYes · 100% structured · mentions 0.3.2Citation fileYes · cites a publicationWebsiteYes · pkgdown
Help pages
16 (1 internal)includes a package overview page
Examples that run
100%1 run in a plain check
Exported functions with examples
10%
Documented parameters
100%
Return-value docs
100%
Help pages citing references
13%

Downloads

3.3K
CRAN downloads in the past year
Rank #17,120 · ~9/day · ~273/mo
Daily download trend is not available in this view yet.
27630 days
73890 days
3.3K1 year
Compare downloads with other packages →
Also on70 r2u4 autocran

Repository

5Stars
3Forks
0Open issues
0Open PRs
4Releases
75Commits
3Commit identities
75 commits · Last activity 2025-04-14 · 0% stars, 30d
Responsiveness
How these are sampled
PRs merged (all time)
100%
Median days to close, 50 most recently updated closed issues
19
Median days to close, 50 most recently updated closed PRs
6

Stars over time

2024-09-24 · 52026-07-25 · 5
PracticesBeta

9 development-tooling and community-health practices detected across 5 families in the upstream repository

Checks run against github.com/petersonr/sparser on 2026-10-18.

Continuous integration (2)
GitHub ActionsR CMD check workflow

The R CMD check workflow runs on Linux

Docs source (4)
README.Rmdpkgdown

GitHub Pages site last deployed 2025-04-14 · The repository has a site deploy workflow

pkgdown site last built 2025-04-14

Coverage (1)
Coverage reporting (Codecov)
CRAN release process (1)
cran-comments.md
Show all practicesHide 1 practice
Lint, format, editor (1)
RStudio project
How this is detected·Detection ruleset v3 (2026-09-26)

Dependencies

Declared dependencies
11 external dependencies (excludes base and recommended)

Installing sparseR adds 55 packages (28 with compiled code, 44 MB of source tarballs). Heaviest: stringi 11 MB, ggplot2 6.0 MB, data.table 5.7 MB.

Depends (1)
R >= 3.5
LinkingTo (0)
none
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

Datasets

People & History

People (1)
Author, Maintainer since 0.2.0 (2022)
Releases (7)

Pick two releases to compare their code metrics.

Package metadata

First published
2022-08-17
Total releases
7 / 4 yrs
License
GPL-3 OSI
Minimum R
≥ 3.5
Bundled data
44 KB / 3 files
Download size
1.8 MB

Cite

Cite this package

Run in R for the authors' entry:

citation("sparseR")

The package provides a citation file, so citation() returns the authors' own entry.

It points to 10.1007/s10182-021-00431-7.

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 sparseR version 0.3.2 [Data set]. HJJB, LLC. Data release v2026-10-21. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-21, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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