wolffd@0:  <h2><a name="models">Supported probabilistic models</h2> 
wolffd@0: <p> 
wolffd@0: It is trivial to implement all of
wolffd@0: the following probabilistic models using the toolbox.
wolffd@0: <ul> 
wolffd@0: <li>Static
wolffd@0: <ul> 
wolffd@0: <li> Linear regression, logistic regression, hierarchical mixtures of experts
wolffd@0:  
wolffd@0: <li> Naive Bayes classifiers, mixtures of Gaussians,
wolffd@0: sigmoid belief nets
wolffd@0:  
wolffd@0: <li> Factor analysis, probabilistic
wolffd@0: PCA, probabilistic ICA, mixtures of these models
wolffd@0:  
wolffd@0: </ul> 
wolffd@0:  
wolffd@0: <li>Dynamic
wolffd@0: <ul> 
wolffd@0:  
wolffd@0: <li> HMMs, Factorial HMMs, coupled HMMs, input-output HMMs, DBNs
wolffd@0:  
wolffd@0: <li> Kalman filters, ARMAX models, switching Kalman filters,
wolffd@0: tree-structured Kalman filters, multiscale AR models
wolffd@0:  
wolffd@0: </ul> 
wolffd@0:  
wolffd@0: <li> Many other combinations, for which there are (as yet) no names!
wolffd@0:  
wolffd@0: </ul> 
wolffd@0:  
wolffd@0: