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SMLE

2.2-3

Joint Feature Screening via Sparse MLE

0packages depend
8.8Kdownloads / year
46.1%test coverage
13/13checks pass

Overview

About
Maintained by Qianxiang ZangFirst published 2020-05-1813 releasesCRAN page ↗

Feature screening is a powerful tool in processing ultrahigh dimensional data. It attempts to screen out most irrelevant features in preparation for a more elaborate analysis. Xu and Chen (2014)doi:10.1080/01621459.2013.879531 proposed an effective screening method SMLE, which naturally incorporates the joint effects among features in the screening process. This package provides an efficient implementation of SMLE-screening for high-dimensional linear, logistic, and Poisson models. The package also provides a function for conducting accurate post-screening feature selection based on an iterative hard-thresholding procedure and a user-specified selection criterion. Zang, Xu, and Burkett (2025)doi:10.18637/jss.v115.i08.

Install

Health

CRAN checks
13OK
Slowest check: 8.4 min · r-oldrel-windows-x86_64
Code health
Yes
Tests · ratio 0.01
46.1%
Coverage · measured lines
100%
Documentation · exports
3
Dependencies · direct
Check history
  • OK2026-08-05
    13 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • NOTE2026-08-01
    12 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • OK2026-03-10
    14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE

Documentation

Documentation
READMENoVignettesYes · dynamicpkgdown siteNoNEWSNoCode of conductNoContributing guideNo
Examples that run
77%
Documented parameters
88%
Return-value docs
100%
References docs
36%

Downloads

8.8K
CRAN downloads in the past year
Rank #5,214 · ~24/day · ~730/mo
Daily download trend is not available in this view yet.
25430 days
1.5K90 days
8.8K1 year
Compare downloads with other packages →
Also on186 r2u20 autocran

Dependencies

Declared dependencies
6 external dependencies (excludes base and recommended)
Depends (1)
R >= 4.0.0
LinkingTo (0)
none
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

Code & Tests

Datasets

People & History

People (3)
Maintainer (1)
Author, Maintainer
Authors (3)
Author, Maintainer
Author
Package Timeline

13 releases. Pick two to compare their code metrics. R releases are shown for context.

  • R
    R 4.6.0 released · 2026-04-24
  • 2.2-3Latest
    2026-01-19 · current release · diff ↗
  • R
    R 4.5.0 released · 2025-04-11
  • 2.2-2
    2025-01-29 · diff ↗
  • R
    R 4.4.0 released · 2024-04-24
  • 2.1-1
    2024-02-12 · diff ↗
  • R
    R 4.3.0 released · 2023-04-21
  • 2.1-0
    2023-01-21 · diff ↗
  • R
    R 4.2.0 released · 2022-04-22
  • 2.0-2
    2021-12-09 · diff ↗
  • 2.0-1
    2021-10-01 · diff ↗
  • 2.0-0
    2021-09-24 · diff ↗
  • 1.2.4
    2021-09-09 · diff ↗
  • 1.2.3
    2021-09-03 · diff ↗
  • R
    R 4.1.0 released · 2021-05-18
  • 1.1.1
    2021-05-09 · diff ↗
Show 4 earlier events
  • 0.4.1
    2020-06-24 · diff ↗
  • 0.4.0
    2020-06-08 · diff ↗
  • 0.3.1
    2020-05-18
  • R
    R 4.0.0 released · 2020-04-24

Package metadata

First published
2020-05-18
Total releases
13 / 6 yrs
License
GPL-3 OSI
Minimum R
≥ 4.0.0
Bundled data
1.5 MB / 2 files
Download size
1.9 MB
Installed size
not tracked yet
With dependencies
not tracked yet

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("SMLE")
Zang, Q., Burkett, K., & Xu, C. (2026). SMLE: Joint Feature Screening via Sparse MLE (Version 2.2-3) [Computer software]. https://doi.org/10.32614/CRAN.package.SMLE

This is what citation() produces when a package has no citation file of its own. If it prints something else, use that.

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 SMLE version 2.2-3 [Data set]. HJJB, LLC. Data release v2026-08-21. https://doi.org/10.5281/zenodo.21843040

From data release v2026-08-21, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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