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").

Expectation-Maximization Binary Clustering

package-ubuntu-20.04-r-4.0.5#cran#EMbC-2.0.3

<p>An ad-hoc object with a set of bivariate data points synthetically generated by sampling from a four component GMM and their corresponding labels indicating which component of the mixture generated each data point.
</p>

<p>See parameter <code>X</code> of the <a href="embc.html">embc</a> constructor.</p>

package-ubuntu-20.04-r-4.0.5#cran#EMbC-2.0.3#docs#x2d

x2d

Description

Format

EMbC

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