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.



  • Distribution.Estimate turned into a multi-parameter type class.
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