Unsupervised, multivariate, binary clustering for meaningful annotation of data, taking into account the uncertainty in the data. A specific constructor for trajectory movement analysis 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: | 2.0.0 |
Imports: | Rcpp (≥ 0.11.0), sp, methods, RColorBrewer, mnormt, maptools |
LinkingTo: | Rcpp, RcppArmadillo |
Suggests: | move, rgl, knitr |
Published: | 2016-11-10 |
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 |
CRAN checks: | EMbC results |
Reference manual: | EMbC.pdf |
Vignettes: |
The EMbC R-package: quick reference |
Package source: | EMbC_2.0.0.tar.gz |
Windows binaries: | r-devel: EMbC_2.0.0.zip, r-release: EMbC_2.0.0.zip, r-oldrel: EMbC_2.0.0.zip |
OS X El Capitan binaries: | r-release: EMbC_2.0.0.tgz |
OS X Mavericks binaries: | r-oldrel: EMbC_2.0.0.tgz |
Old sources: | EMbC archive |
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