treeHFM (1.0.3)

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Hidden Factor Graph Models.

Hidden Factor graph models generalise Hidden Markov Models to tree structured data. The distinctive feature of 'treeHFM' is that it learns a transition matrix for first order (sequential) and for second order (splitting) events. It can be applied to all discrete and continuous data that is structured as a binary tree. In the case of continuous observations, 'treeHFM' has Gaussian distributions as emissions.

Maintainer: Henrik Failmezger
Author(s): Henrik Failmezger, Achim Tresch

License: GPL (>= 2)

Uses: mclust

Released over 3 years ago.

3 previous versions



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