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Movement to Behaviour Inference using Random Forest

0packages depend
3.8Kdownloads / year
–test coverage
13/13flavors OK

Overview

About

Prediction of behaviour from movement characteristics using observation and random forest for the analyses of movement data in ecology. From movement information (speed, bearing...) the model predicts the observed behaviour (movement, foraging...) using random forest. The model can then extrapolate behavioural information to movement data without direct observation of behaviours. The specificity of this method relies on the derivation of multiple predictor variables from the movement data over a range of temporal windows. This procedure allows to capture as much information as possible on the changes and variations of movement and ensures the use of the random forest algorithm to its best capacity. The method is very generic, applicable to any set of data providing movement data together with observation of behaviour.

Install

Health

CRAN checks
13OK
Slowest check: 2.4 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 1.1.0
READMEYes · 312 wordsVignettesYes · 1 · dynamicNEWSNoCitation fileNoWebsitenot declared in DESCRIPTION
Help pages
16 (1 internal)includes a package overview page
Examples that run
63%5 run in a plain check · 3 never run
Exported functions with examples
70%
Documented parameters
100%
Return-value docs
60%
Help pages citing references
0%
Vignettes (1)

Downloads

3.8K
CRAN downloads in the past year
Rank #13,675 · ~10/day · ~313/mo
Daily download trend is not available in this view yet.
33230 days
84390 days
3.8K1 year
Compare downloads with other packages →
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Repository

2Stars
1Forks
1Open issues
0Open PRs
0Releases
22Commits
2Commit identities
22 commits · Last activity 2025-06-24 · 0% stars, 30d
Responsiveness
not measured

Stars over time

2022-04-27 · 22026-07-07 · 2
PracticesBeta

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

Checks run against github.com/ldbk/m2b on 2026-10-18.

CRAN release process (2)
cran-comments.mdCRAN-SUBMISSION
How this is detected·Detection ruleset v3 (2026-09-26)

Dependencies

Declared dependencies
10 external dependencies (excludes base and recommended)

Installing m2b adds 67 packages (38 with compiled code, 49 MB of source tarballs). Heaviest: stringi 11 MB, ggplot2 6.0 MB, data.table 5.7 MB.

Depends (1)
R >= 3.3.0
Imports (8)
LinkingTo (0)
none
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

Datasets

People & History

People (2)
Author, Maintainer since 1.0 (2017)
Releases (2)

Pick two releases to compare their code metrics.

  • R
    R 4.6.0 released · 2026-04-24
  • unarchivedReturned to CRAN
    2025-06-25
  • 1.1.0Latest
    record
    2025-06-25 · current release · diff ↗
  • archivedRemoved from CRAN
    2025-06-13
    issues were not corrected despite reminders
  • R
    R 4.5.0 released · 2025-04-11
  • 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
  • 1.0
    record
    2017-05-04
  • R
    R 3.4.0 released · 2017-04-21

Package metadata

First published
2017-05-04
Total releases
2 / 9 yrs
License
GPL-3 OSI
Minimum R
≥ 3.3.0
Bundled data
44 KB / 1 file
Download size
407 KB

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("m2b")
Dubroca, L., & Thiebault, A. (2025). m2b: Movement to Behaviour Inference using Random Forest (Version 1.1.0) [Computer software]. https://doi.org/10.32614/CRAN.package.m2b

This package has no citation file, so citation() returns this entry built from DESCRIPTION.

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 m2b version 1.1.0 [Data set]. HJJB, LLC. Data release v2026-10-20. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-20, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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