STCpartitions-class

<dl class="dl-horizontal">
 <dt>hardind</dt><dd>numeric. It indicates the hard partition of the individuals (obtained by the MAP rule qpplied with the MLE).</dd>
 <dt>fuzzyind</dt><dd>matrix. It indicates the fuzzy partition (conditional probability of the component membership) of the individuals.</dd>
 <dt>hardseg</dt><dd>list. It indicates the segmentation (most probable polynom according to the spatial and temporal grid) per components</dd>
</dl>

Mixture model is used to achieve the clustering goal. Each component is itself a mixture model of polynomial autoregressive regressions whose the logistic weights consider the spatial and temporal information.

Matthieu Marbac

SpaTimeClus

Model-Based Clustering of Spatio-Temporal Data

STCpartitions-class function

<dl class='dl-horizontal'>
 <dt>hardind</dt><dd>numeric. It indicates the hard partition of the individuals (obtained by the MAP rule qpplied with the MLE).</dd>
 <dt>fuzzyind</dt><dd>matrix. It indicates the fuzzy partition (conditional probability of the component membership) of the individuals.</dd>
 <dt>hardseg</dt><dd>list. It indicates the segmentation (most probable polynom according to the spatial and temporal grid) per components</dd>
</dl>

Constructor of [<code><a href='<a href='STCpartitions'></a>'>STCpartitions</a></code>] class — STCpartitions-class

Constructor of [<code><a href='<a href='STCpartitions'></a>'>STCpartitions</a></code>] class

Constructor of [<code><a href="/link/?package=SpaTimeClus&version=1.0.1" stcpartitions'="" data-mini-rdoc="SpaTimeClus::"></a>'>STCpartitions</code>] class

STCpartitions-class: Constructor of [`'>STCpartitions`] class

Description

Arguments

Examples