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TemporalForest

0.1.4

Network-Guided Temporal Forests for Feature Selection in High-Dimensional Longitudinal Data

0packages depend
3.3Kdownloads / year
test coverage
13/13checks pass

Overview

About
Maintained by Sisi ShaoFirst published 2025-12-221 releasesCRAN page ↗GitHub ↗

Implements the Temporal Forest algorithm for feature selection in high-dimensional longitudinal data. The method combines time-aware network construction via weighted gene co-expression network analysis (WGCNA), module-based feature screening, and stability selection using tree-based models. This package provides tools for reproducible longitudinal analysis, closely following the methodology described in Shao, Moore, and Ramirez (2025) https://github.com/SisiShao/TemporalForest.

Install

Health

CRAN checks
13OK
Slowest check: 4.4 min · r-oldrel-macos-x86_64
Code health
None
Tests · ratio 0.00
not tracked
Coverage
83%
Documentation · exports
8
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
  • OK2026-06-09
    13 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • ERROR2026-06-08
    12 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
  • OK2026-03-10
    14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE

Documentation

Documentation
READMEYes · 262 wordsVignettesYes · dynamicpkgdown siteNoNEWSNoCode of conductNoContributing guideNo
Examples that run
83%
Documented parameters
100%
Return-value docs
100%
References docs
11%

Downloads

3.3K
CRAN downloads in the past year
Rank #9,454 · ~9/day · ~275/mo
Daily download trend is not available in this view yet.
19430 days
99590 days
3.3K1 year
Compare downloads with other packages →
Also on47 r2u

Repository

Repository
0Stars
0Forks
0Open issues
0Open PRs
0Releases
Last activity 2025-12-22

Repository practices

Upstream repositoryBeta

1 development-tooling and community-health practice detected across 1 family in the upstream repository

Checks run against github.com/sisishao/temporalforest on 2026-08-16.

Lint, format, editor (1)
RStudio project
How this is detected·Detection ruleset v1 (2026-07-18)

Dependencies

Declared dependencies
8 external dependencies (excludes base and recommended)
Depends (1)
R >= 3.5.0
Imports (8)
LinkingTo (0)
none
Suggests (5)
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

Code & Tests

People & History

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

1 release. R releases are shown for context.

  • R
    R 4.6.0 released · 2026-04-24
  • 0.1.4Latest
    2026-03-10 · current release
  • R
    R 4.5.0 released · 2025-04-11

Package metadata

First published
2025-12-22
Total releases
1 / 1 yrs
License
MIT + file LICENSE OSI
Minimum R
≥ 3.5.0
Download size
3.2 MB
Installed size
not tracked yet
With dependencies
not tracked yet

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("TemporalForest")
Shao, S., Moore, J. H., & Ramirez, C. M. (2025). TemporalForest: Network-Guided Temporal Forests for Feature Selection in High-Dimensional Longitudinal Data (Version 0.1.4) [Computer software]. https://doi.org/10.32614/CRAN.package.TemporalForest

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 TemporalForest version 0.1.4 [Data set]. HJJB, LLC. Data release v2026-08-18. https://doi.org/10.5281/zenodo.21843040

From data release v2026-08-18, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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