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m2b
View on CRAN: Click
here
Download and install m2b package within the R console
Install from CRAN:
install.packages("m2b")
Install from Github:
library("remotes")
install_github("cran/m2b")
Install by package version:
library("remotes")
install_version("m2b", "1.0")
Attach the package and use:
library("m2b")
Maintained by
Laurent Dubroca
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2017-05-03
Latest Update: 2017-05-03
Description:
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.
How to cite:
Laurent Dubroca (2017). m2b: Movement to Behaviour Inference using Random Forest. R package version 1.0, https://cran.r-project.org/web/packages/m2b
Previous versions and publish date:
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Other R packages that m2b depends,
imports, suggests or enhances
Functions, R codes and Examples using
the m2b R package
Some associated functions: dxyt . dxyt2 . extractRF . ltraj2xytb . m2b . modelRF . plot-methods . resB . resRF . shiftvalue . test . track_CAGA_005 . xytb-class . xytb-methods . xytb2hmm . xytb2ltraj .
Some associated R codes: data.R . m2b.R . xytb-class.R . Full m2b package functions and examples
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