Package: treeHFM
Version: 1.0.0.1
Date: 2016-06-4
Title: Hidden Factor Graph Models
Author: Henrik Failmezger, Achim Tresch
Maintainer: Henrik Failmezger <Henrik.Failmezger@googlemail.com>
Depends: mclust
Collate: HFMfit.R HFMviterbi.R DrawViterbiTree.R
Description: 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.
License: GPL (>= 2)
biocViews: HiddenMarkovModel, Clustering
LazyLoad: yes
Packaged: 2016-07-08 08:52:44 UTC; ripley
NeedsCompilation: yes
Repository: CRAN
Date/Publication: 2016-07-08 11:11:54
