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EMbC: Expectation-Maximization Binary Clustering

Unsupervised, multivariate, binary clustering for meaningful annotation of data, taking into account the uncertainty in the data. A specific constructor for trajectory analysis in movement ecology yields behavioural annotation of trajectories based on estimated local measures of velocity and turning angle, eventually with solar position covariate as a daytime indicator, ("Expectation-Maximization Binary Clustering for Behavioural Annotation").

Version: 2.0.4
Imports: Rcpp (≥ 0.11.0), sp, methods, RColorBrewer, mnormt, suntools
LinkingTo: Rcpp, RcppArmadillo
Suggests: move, sf, rgl, knitr
Published: 2023-10-03
DOI: 10.32614/CRAN.package.EMbC
Author: Joan Garriga, John R.B. Palmer, Aitana Oltra, Frederic Bartumeus
Maintainer: Joan Garriga <jgarriga at ceab.csic.es>
License: GPL-3 | file LICENSE
URL: <doi:10.1371/journal.pone.0151984>
NeedsCompilation: yes
Materials: NEWS
In views: SpatioTemporal, Tracking
CRAN checks: EMbC results

Documentation:

Reference manual: EMbC.pdf
Vignettes: The EMbC R-package: quick reference

Downloads:

Package source: EMbC_2.0.4.tar.gz
Windows binaries: r-devel: EMbC_2.0.4.zip, r-release: EMbC_2.0.4.zip, r-oldrel: EMbC_2.0.4.zip
macOS binaries: r-release (arm64): EMbC_2.0.4.tgz, r-oldrel (arm64): EMbC_2.0.4.tgz, r-release (x86_64): EMbC_2.0.4.tgz, r-oldrel (x86_64): EMbC_2.0.4.tgz
Old sources: EMbC archive

Reverse dependencies:

Reverse suggests: move

Linking:

Please use the canonical form https://CRAN.R-project.org/package=EMbC to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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