Hidden Markov Models using LAPACK primitives

Version on this page:0.4@rev:1
LTS Haskell 21.13:
Stackage Nightly 2023-09-25:
Latest on Hackage:

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BSD-3-Clause licensed by Henning Thielemann
This version can be pinned in stack with:hmm-lapack-0.4@sha256:e78475215e310bb6c7a288d5498098642b2472bd57bdeff51c69ed6c8d06af81,3096

Hidden Markov Models implemented using LAPACK data types and operations.

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.