transition.heatmap

Plots a heatmap of an HMM's initial and transition probabilities.

Provides an implementation of a mixture of hidden Markov models
(HMMs) for discrete sequence data in the Discrete Bayesian HMM Clustering
(DBHC) algorithm. The DBHC algorithm is an HMM Clustering
algorithm that finds a mixture of discrete-output HMMs while using
heuristics based on Bayesian Information Criterion (BIC) to search for the
optimal number of HMM states and the optimal number of clusters.

Gabriel Budel

DBHC

Sequence Clustering with Discrete-Output HMMs

transition.heatmap function

<dl><dt>transition</dt>
<dd>A matrix with transition probabilities (see also
<code>build_hmm</code>).</dd>
<dt>initial</dt>
<dd>An (optional) vector of initial probabilities.</dd>
<dt>base_size</dt>
<dd>Numerical, a size parameter for the plots made using <code>ggplot2</code>
(see <a href="https://ggplot2.tidyverse.org/reference/theme.html">theme</a>), default = 10.</dd></dl>

Arguments

Heatmap Transition Probabilities — transition.heatmap

<dl>

<dt>transition</dt>
<dd>A matrix with transition probabilities (see also
<code>build_hmm</code>).</dd>


<dt>initial</dt>
<dd>An (optional) vector of initial probabilities.</dd>


<dt>base_size</dt>
<dd>Numerical, a size parameter for the plots made using <code>ggplot2</code>
(see <a href='https://ggplot2.tidyverse.org/reference/theme.html'>theme</a>), default = 10.</dd>

</dl>

transition.heatmap: Heatmap Transition Probabilities

Description

Usage

Arguments

See Also