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 <h2><a name="models">Supported probabilistic models</h2> 
<p> 
It is trivial to implement all of
the following probabilistic models using the toolbox.
<ul> 
<li>Static
<ul> 
<li> Linear regression, logistic regression, hierarchical mixtures of experts
 
<li> Naive Bayes classifiers, mixtures of Gaussians,
sigmoid belief nets
 
<li> Factor analysis, probabilistic
PCA, probabilistic ICA, mixtures of these models
 
</ul> 
 
<li>Dynamic
<ul> 
 
<li> HMMs, Factorial HMMs, coupled HMMs, input-output HMMs, DBNs
 
<li> Kalman filters, ARMAX models, switching Kalman filters,
tree-structured Kalman filters, multiscale AR models
 
</ul> 
 
<li> Many other combinations, for which there are (as yet) no names!
 
</ul>