Clustering of high dimensional data with Hidden Markov Model on Variable Blocks (HMM-VB) fitted via Baum-Welch algorithm. Clustering is performed by the Modal Baum-Welch algorithm (MBW), which finds modes of the density function. Lin Lin and Jia Li (2017) <http://jmlr.org/papers/v18/16-342.html>.

Clustering High Dimensional Data with Hidden Markov Model on
Variable Blocks

package-ubuntu-20.04-r-4.0.5#cran#HDclust-1.0.3

<p>This function outputs a list with means, covariance matrices, inverse covarince matrices and
logarithms of the determinants of the covariance matrices for all states of the HMM.
</p>

<table summary="R argblock"><tr valign="top">
<td><code>object</code></td>
<td>
<p>Object of class "HMM".</p>
</td>
</tr></table>

package-ubuntu-20.04-r-4.0.5#cran#HDclust-1.0.3#docs#getHmmParam

getHmmParam

Description

Usage

Arguments

HDclust

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