Unsupervised, multivariate, clustering algorithm for meaningful binary clustering and taking into account the uncertainty in the data. A specific constructor for trajectory movement analysis yields behavioural annotation of the tracks based on estimated local measures of velocity and turning angle, eventually with solar position covariate as a daytime indicator.
| Version: | 1.9.4 |
| Depends: | move |
| Imports: | sp, methods, RColorBrewer, mnormt, maptools |
| Suggests: | rgl, knitr |
| Published: | 2016-03-22 |
| 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: | 'Expectation-Maximization Binary Clustering for Behavioural Annotation', (submitted to PLOS ONE) |
| NeedsCompilation: | no |
| Materials: | NEWS |
| CRAN checks: | EMbC results |
| Reference manual: | EMbC.pdf |
| Vignettes: |
The EMbC R-package: quick reference |
| Package source: | EMbC_1.9.4.tar.gz |
| Windows binaries: | r-devel: EMbC_1.9.4.zip, r-release: EMbC_1.9.4.zip, r-oldrel: EMbC_1.9.4.zip |
| OS X Mavericks binaries: | r-release: EMbC_1.9.4.tgz, r-oldrel: EMbC_1.9.4.tgz |
| Old sources: | EMbC archive |
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