Skip to content

Dual Feature Reduction for SGL

0packages depend
2.4Kdownloads / year
62.6%test coverage
13/13flavors OK

Overview

About

Implementation of the Dual Feature Reduction (DFR) approach for the Sparse Group Lasso (SGL) and the Adaptive Sparse Group Lasso (aSGL) (Feser and Evangelou (2024) doi:10.48550/arXiv.2405.17094). The DFR approach is a feature reduction approach that applies strong screening to reduce the feature space before optimisation, leading to speed-up improvements for fitting SGL (Simon et al. (2013) doi:10.1080/10618600.2012.681250) and aSGL (Mendez-Civieta et al. (2020) doi:10.1007/s11634-020-00413-8 and Poignard (2020) doi:10.1007/s10463-018-0692-7) models. DFR is implemented using the Adaptive Three Operator Splitting (ATOS) (Pedregosa and Gidel (2018) doi:10.48550/arXiv.1804.02339) algorithm, with linear and logistic SGL models supported, both of which can be fit using k-fold cross-validation. Dense and sparse input matrices are supported.

Install

Health

CRAN checks
13OK
Slowest check: 4.8 min · r-oldrel-windows-x86_64
Status changes
  • OK13 OK2026-08-05
  • NOTE12 OK, 1 NOTE2026-08-01
  • OK13 OK2026-06-09
  • ERROR12 OK, 1 ERROR2026-06-08
  • OK13 OK2026-05-02
Show 2 earlier changesHide 2 earlier changes
  • ERROR11 OK, 1 ERROR2026-04-25
  • OK14 OK2026-03-10
Advisories

none known

Documentation

In release 0.1.6
READMEYes · 273 wordsVignettesNoNEWSNoCitation fileYes · cites a publicationWebsitenot declared in DESCRIPTION
Help pages
8 (1 internal)includes a package overview page
Examples that run
100%7 run in a plain check
Exported functions with examples
100%
Documented parameters
100%
Return-value docs
100%
Help pages citing references
50%

Downloads

2.4K
CRAN downloads in the past year
Rank #17,412 · ~7/day · ~204/mo
Daily download trend is not available in this view yet.
29730 days
73990 days
2.4K1 year
Compare downloads with other packages →
Also on84 r2u11 autocran

Repository

1Stars
0Forks
2Open issues
0Open PRs
0Releases
9Commits
1Commit identities
9 commits · Last activity 2026-06-28
Responsiveness
How these are sampled
PRs merged (all time)
not measured
Median days to close, 50 most recently updated closed issues
96
Median days to close, 50 most recently updated closed PRs
not measured

Stars over time

2024-09-24 · 12026-07-07 · 1
PracticesBeta

2 development-tooling and community-health practices detected across 2 families in the upstream repository

Checks run against github.com/ff1201/dfr on 2026-10-21.

CRAN release process (1)
cran-comments.md
Lint, format, editor (1)
RStudio project
How this is detected·Detection ruleset v4 (2026-10-20)

Dependencies

Declared dependencies
6 external dependencies (excludes base and recommended)

Installing dfr adds 72 packages (40 with compiled code, 66 MB of source tarballs). Heaviest: BH 14 MB, stringi 11 MB, ggplot2 6.0 MB.

Depends (0)
none
Imports (8)
sgscaretMASSmethodsstatsgrDevicesgraphicsMatrix
LinkingTo (0)
none
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

People & History

People (1)
Author, Maintainer since 0.1.0 (2024)
Releases (7)

Pick two releases to compare their code metrics.

  • R
    R 4.6.0 released · 2026-04-24
  • 0.1.6Latest
    record
    2025-09-30 · current release · diff ↗
  • R
    R 4.5.0 released · 2025-04-11
  • 0.1.5
    record
    2025-03-06 · diff ↗
  • 0.1.4
    record
    2025-02-06 · diff ↗
  • 0.1.3
    record
    2025-02-03 · diff ↗
  • 0.1.2
    record
    2024-11-28 · diff ↗
  • unarchivedReturned to CRAN
    2024-11-16
  • 0.1.1
    record
    2024-11-16 · diff ↗
  • archivedRemoved from CRAN
    2024-11-05
    requires archived package 'faux'
  • 0.1.0
    record
    2024-09-26
  • R
    R 4.4.0 released · 2024-04-24

Package metadata

First published
2024-09-26
Total releases
7 / 2 yrs
License
GPL (>= 3) OSI
Download size
81 KB

Cite

Cite this package

Run in R for the authors' entry:

citation("dfr")

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

It points to 10.48550/arxiv.2405.17094.

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 dfr version 0.1.6 [Data set]. HJJB, LLC. Data release v2026-10-24. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-24, which the citation names so these numbers can be found later. More on citing and the projects behind them.

Report a problem with this page →

Privacy choices

These apply to this browser and are stored on this device only. Nothing about your choice is sent to us.

Read the privacy policy