Hidden Markov Models implemented using LAPACK data types and operations.
http://en.wikipedia.org/wiki/Hidden_Markov_Model

It implements:

generation of samples of emission sequences,

computation of the likelihood of an observed sequence of emissions,

construction of most likely state sequence
that produces an observed sequence of emissions,

supervised and unsupervised training of the model by Baum-Welch algorithm.

It supports any kind of emission distribution,
where discrete and multivariate Gaussian distributions
are implemented as examples.

For an introduction please refer to the examples:

`Math.HiddenMarkovModel.Example.TrafficLight`

`Math.HiddenMarkovModel.Example.SineWave`

`Math.HiddenMarkovModel.Example.Circle`

An alternative package without foreign calls is `hmm`

.