Package: m2b 1.0

m2b: Movement to Behaviour Inference using Random Forest

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.

Authors:Laurent Dubroca [aut, cre], Andréa Thiebault [aut]

m2b_1.0.tar.gz
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m2b.pdf |m2b.html✨
m2b/json (API)

# Install 'm2b' in R:
install.packages('m2b', repos = c('https://ldbk.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/ldbk/m2b/issues

Datasets:
  • track_CAGA_005 - Data collected from a cape gannet track (_Morus capensis_, Lichtenstein 1823), breeding on Bird Island (Algo Bay, South Africa) in december 2010.

On CRAN:

12 exports 2 stars 1.15 score 80 dependencies 1 mentions 12 scripts 780 downloads

Last updated 7 years agofrom:9fc5404d1d. Checks:OK: 1 NOTE: 6. Indexed: yes.

TargetResultDate
Doc / VignettesOKAug 28 2024
R-4.5-winNOTEAug 28 2024
R-4.5-linuxNOTEAug 28 2024
R-4.4-winNOTEAug 28 2024
R-4.4-macNOTEAug 28 2024
R-4.3-winNOTEAug 28 2024
R-4.3-macNOTEAug 28 2024

Exports:dxytdxyt2extractRFltraj2xytbmodelRFplotresBresRFshiftvaluexytbxytb2hmmxytb2ltraj

Dependencies:bitopscaretcaToolsclasscliclockcodetoolscolorspacecpp11data.tablediagramdigestdplyre1071fansifarverforeachfuturefuture.applygenericsgeosphereggplot2globalsgluegowergtablehardhatipredisobanditeratorsKernSmoothlabelinglatticelavalifecyclelistenvlubridatemagrittrMASSMatrixmgcvModelMetricsmunsellnlmennetnumDerivparallellypillarpkgconfigplyrpROCprodlimprogressrproxypurrrR6randomForestRColorBrewerRcpprecipesreshape2rlangrpartscalesshapespSQUAREMstringistringrsurvivaltibbletidyrtidyselecttimechangetimeDatetzdbutf8vctrsviridisLitewithr

m2b tutorial

Laurent Dubroca, Andréa Thiebault

Rendered fromtutorial.Rmdusingknitr::rmarkdownon Aug 28 2024.

Last update: 2017-05-16
Started: 2017-02-28

Readme and manuals

Help Manual

Help pageTopics
internal functiondxyt
internal functiondxyt2
Extract the random forest model from an xytb objectextractRF
ltraj object conversion to xytb objectltraj2xytb
Movement to behaviour packagem2b-package m2b
xytb randomForest functionmodelRF
xytb plot methodplot plot,xytb,missing-method
Representation of the predicted vs observed behaviour of an xytb objectresB
Random forest model outputs for a xytb objectresRF
internal functionshiftvalue
Data collected from a cape gannet track (_Morus capensis_, Lichtenstein 1823), breeding on Bird Island (Algo Bay, South Africa) in december 2010.track_CAGA_005
xytb class constructorxytb xytb,data.frame,character xytb,data.frame,character,ANY,ANY,ANY-method xytb,data.frame,character,vector,vector xytb,data.frame,character,vector,vector,ANY-method xytb,data.frame,character,vector,vector,vector xytb,data.frame,character,vector,vector,vector-method xytb,missing,missing,ANY,ANY,ANY-method
xytb class definitionxytb-class
xytb object conversion to moveHMM objectxytb2hmm
xytb class conversion to ltraj objectxytb2ltraj