Sorted L1 Penalized Estimation
Overview
Efficient implementations for Sorted L-One Penalized Estimation (SLOPE): generalized linear models regularized with the sorted L1-norm (Bogdan et al. 2015). Supported models include ordinary least-squares regression, binomial regression, multinomial regression, and Poisson regression. Both dense and sparse predictor matrices are supported. In addition, the package features predictor screening rules that enable fast and efficient solutions to high-dimensional problems.
Install
Health
- OK13 OK2026-09-08
- ERROR12 OK, 1 ERROR2026-09-07
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK12 OK2026-04-25
Show 3 earlier changesHide 3 earlier changes
- NOTE12 OK, 2 NOTE2026-04-22
- ERROR11 OK, 2 NOTE, 1 ERROR2026-04-18
- NOTE12 OK, 2 NOTE2026-03-10
Documentation
- Help pages
- 30 (5 internal)includes a package overview page
- Examples that run
- 100%16 run in a plain check
- Exported functions with examples
- 89%
- Documented parameters
- 97%
- Return-value docs
- 100%
- Help pages citing references
- 3%
- An introduction to SLOPE HTML
- Models in SLOPE HTML
- Solvers in SLOPE HTML
Downloads
Repository
- PRs merged (all time)
- 80%
- Median days to close, 50 most recently updated closed issues
- 36
- Median days to close, 50 most recently updated closed PRs
- 0
Stars over time
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Releases over time
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Commits over time
15 development-tooling and community-health practices detected across 9 families in the upstream repository
Checks run against github.com/jolars/slope on 2026-10-18.
The R CMD check workflow runs on Linux, macOS and Windows, and on R-devel
The repository owner accepts GitHub Sponsors
GitHub Pages site last deployed 2026-10-09 · The repository has a site deploy workflow
pkgdown site last built 2026-10-09
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This repository shows signs of AI coding tools.
- Claude Codefirst seen 2026-06-02Seen in the repository: CLAUDE.mdNamed in .Rbuildignore: CLAUDE.md
Dependencies
Installing SLOPE adds 6 packages (4 with compiled code, 18 MB of source tarballs). Heaviest: BH 14 MB, Rcpp 1.8 MB, RcppEigen 1.7 MB.
Code & Tests
Datasets
People & History
Previously maintained by Evan Patterson (0.1.1 to 0.1.3).
Pick two releases to compare their code metrics.
- 2.1.1Latest
- RR 4.6.0 released · 2026-04-24
- 2.1.02026-03-28 · diff ↗
- 2.0.0
- 1.2.02025-11-11 · diff ↗
- 1.1.02025-10-30 · diff ↗
- 1.0.12025-07-02 · diff ↗
- 1.0.0
- RR 4.5.0 released · 2025-04-11
- 0.5.22025-02-02 · diff ↗
- 0.5.12024-07-09 · diff ↗
- RR 4.4.0 released · 2024-04-24
- RR 4.3.0 released · 2023-04-21
- 0.5.02022-06-10 · diff ↗
- RR 4.2.0 released · 2022-04-22
- 0.4.12022-03-14 · diff ↗
Show 14 earlier eventsHide 14 earlier events
- 0.4.0
- RR 4.1.0 released · 2021-05-18
- 0.3.32021-03-17 · diff ↗
- 0.3.22020-07-10 · diff ↗
- 0.3.0
- RR 4.0.0 released · 2020-04-24
- 0.2.12020-04-16 · diff ↗ ·
removed 1 export
SLOPE_solver_matlabadded 4 exports
caretSLOPE, plotDiagnostics, score, trainSLOPE - RR 3.6.0 released · 2019-04-26
- RR 3.5.0 released · 2018-04-23
- RR 3.4.0 released · 2017-04-21
- RR 3.3.0 released · 2016-05-03
- 0.1.32015-11-03 · diff ↗
- 0.1.12015-04-27
- RR 3.2.0 released · 2015-04-16
Package metadata
- First published
- 2015-04-27
- Total releases
- 18 / 11 yrs
- License
- GPL-3 OSI
- Minimum R
- ≥ 4.1.0
- Bundled data
- 55 KB / 6 files
- Download size
- 489 KB
Cite
Cite this package
Run in R for the authors' entry:
citation("SLOPE")The package provides a citation file, so citation() returns the authors' own entry.
It points to 10.48550/arxiv.2511.02430, 10.1214/15-aoas842.
The repository also keeps a CITATION.cff.
Cite the R Observatory
For a number measured here: a download total, a coverage figure, an archival date.
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.