## Supported probabilistic models

It is trivial to implement all of the following probabilistic models using the toolbox.

- Static
  - Linear regression, logistic regression, hierarchical mixtures of experts
  - Naive Bayes classifiers, mixtures of Gaussians, sigmoid belief nets
  - Factor analysis, probabilistic PCA, probabilistic ICA, mixtures of these models
- Dynamic
  - HMMs, Factorial HMMs, coupled HMMs, input-output HMMs, DBNs
  - Kalman filters, ARMAX models, switching Kalman filters, tree-structured Kalman filters, multiscale AR models
- Many other combinations, for which there are (as yet) no names!