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").


EMbC 2.0.1

Bug fixes

- Corrected a bug in the post-smoothing function (thanks to Simona Imperio for noting it). Also, we have added a method in the post-smoothing function for binClstStck instances.

EMbC 2.0.0

Major improvements

  • Some core functionalities have been implemented using Rcpp. This results in a significant increase in computational speed when using large datasets.

  • With the aim of enhancing the EMbC R-package as a real general purpose algorithm, the dependency with respect to the move R-package has been dropped. Thus, potential users coming from domains other than ecology are not forced to install packages that are not desired. However, Move objects from the move R-package can still be used directly as input data.

Bug fixes

  • The bg parameter of the sctr function is working properly now.

EMbC 1.9.4

Bug fixes

  • When working with move objects, version 1.9.3 was picking GMT timestamps instead of using study local timestamps. This has been changed in version 1.9.4. Of note: the example in the vignette illustrating the use of move objects was affected by this error.

Minor improvements

  • The command view was depicting the trajectory without taking into account the proportionality of the axes. This has been corrected in version 1.9.4.

  • In the multivarite case, commands view() and sctr() depict plots with a light-grey background colour to enhance the visibility of the data points. We added a bg parameter to allow changing this default behaviour.

Reference manual

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2.0.3 by Joan Garriga, 2 years ago

Browse source code at https://github.com/cran/EMbC

Authors: Joan Garriga , John R.B. Palmer , Aitana Oltra , Frederic Bartumeus

Documentation:   PDF Manual  

Task views: Handling and Analyzing Spatio-Temporal Data, Processing and Analysis of Tracking Data

GPL-3 | file LICENSE license

Imports Rcpp, sp, methods, RColorBrewer, mnormt, maptools

Suggests move, rgl, knitr

Linking to Rcpp, RcppArmadillo

Suggested by move.

See at CRAN