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opticut

0.1-4

Likelihood Based Optimal Partitioning and Indicator Species Analysis

0packages depend
3.2Kdownloads / year
90.8%test coverage
13/13checks pass

Overview

About
Maintained by Peter SolymosFirst published 2016-12-175 releasesCRAN page ↗GitHub ↗

Likelihood based optimal partitioning and indicator species analysis. Finding the best binary partition for each species based on model selection, with the possibility to take into account modifying/confounding variables as described in Kemencei et al. (2014) doi:10.1556/ComEc.15.2014.2.6. The package implements binary and multi-level response models, various measures of uncertainty, Lorenz-curve based thresholding, with native support for parallel computations.

Install

Health

CRAN checks
13OK
Slowest check: 8.4 min · r-oldrel-windows-x86_64
Code health
Yes
Tests · ratio 0.24
90.8%
Coverage · measured lines
100%
Documentation · exports
7
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
  • OK2026-06-08
    13 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • NOTE2026-06-07
    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
READMENoVignettesNopkgdown siteNoNEWSNoCode of conductNoContributing guideNo
Examples that run
100%
Documented parameters
92%
Return-value docs
100%
References docs
40%

Downloads

3.2K
CRAN downloads in the past year
Rank #17,322 · ~9/day · ~264/mo
Daily download trend is not available in this view yet.
16030 days
61990 days
3.2K1 year
Compare downloads with other packages →
Also on98 r2u14 autocran

Repository

Repository
2Stars
1Forks
4Open issues
0Open PRs
2Releases
851Commits
1Contributors
cranspeciesindicator-species-analysislikelihoodoptimal-partitioningrecology
851 commits · Last activity 2026-04-25

Stars over time

2020-12-25 · 12026-07-07 · 2

Repository practices

Upstream repositoryBeta

3 development-tooling and community-health practices detected across 3 families in the upstream repository

Checks run against github.com/psolymos/opticut on 2026-08-16.

Continuous integration (1)
GitHub Actions
Lint, format, editor (1)
RStudio project
Git structural (1)
.gitattributes
How this is detected·Detection ruleset v1 (2026-07-18)

Dependencies

Declared dependencies
5 external dependencies (excludes base and recommended)
Depends (2)
R >= 3.1.0pbapply
Imports (6)
LinkingTo (0)
none
Suggests (0)
none
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

Code & Tests

People & History

People (2)
Maintainer (1)
Author, Maintainer
Authors (1)
Author, Maintainer
Contributors (1)
Contributor
Listed in earlier versions (2)
no longer listed · 0.1-3
no longer listed · 0.1-4
Package Timeline

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

  • R
    R 4.6.0 released · 2026-04-24
  • 0.1-4Latest
    2025-07-14 · current release · diff ↗
  • R
    R 4.5.0 released · 2025-04-11
  • 0.1-3
    2024-05-22 · diff ↗
  • R
    R 4.4.0 released · 2024-04-24
  • R
    R 4.3.0 released · 2023-04-21
  • R
    R 4.2.0 released · 2022-04-22
  • R
    R 4.1.0 released · 2021-05-18
  • R
    R 4.0.0 released · 2020-04-24
  • R
    R 3.6.0 released · 2019-04-26
  • R
    R 3.5.0 released · 2018-04-23
  • 0.1-2
    2018-02-01 · diff ↗
  • 0.1-1
    2018-01-31 · diff ↗
  • R
    R 3.4.0 released · 2017-04-21
  • 0.1-0
    2016-12-17
  • R
    R 3.3.0 released · 2016-05-03

Package metadata

First published
2016-12-17
Total releases
5 / 10 yrs
License
GPL-2 OSI
Minimum R
≥ 3.1.0
Bundled data
132 KB / 3 files
Download size
186 KB
Installed size
not tracked yet
With dependencies
not tracked yet

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("opticut")
Solymos, P., & Azeria, E. T. (2025). opticut: Likelihood Based Optimal Partitioning and Indicator Species Analysis (Version 0.1-4) [Computer software]. https://doi.org/10.32614/CRAN.package.opticut

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 opticut 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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