treeHFM: 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.

Install the latest version of this package by entering the following in R:
install.packages("treeHFM")
AuthorHenrik Failmezger, Achim Tresch
Bioconductor views Clustering HiddenMarkovModel
Date of publication2016-09-19 01:45:39
MaintainerHenrik Failmezger <Henrik.Failmezger@googlemail.com>
LicenseGPL (>= 2)
Version1.0.3

View on CRAN

Files

src
src/RWrapperFunctions.cpp
src/Makevars
src/RWrapperFunctions.h
src/RWrapperBM.cpp
src/MaxSum.h
src/FactorGraph.h
src/matUtils.h
src/helpFunctions.cpp
src/BaumWelch.h
src/matUtils.cpp
src/MemoryAllocation.cpp
src/ParamContainerEmissions.cpp
src/MultivariateGaussian.cpp
src/EmissionFunction.cpp
src/helpFunctions.h
src/BaumWelch.cpp
src/MultivariateGaussian.h
src/EmissionFunction.h
src/MemoryAllocation.h
src/RWrapperMS.cpp
src/SumProduct.cpp
src/FactorGraph.cpp
src/SumProduct.h
src/DebugConstants.h
src/ParamContainerEmissions.h
src/MaxSum.cpp
NAMESPACE
R
R/HFMviterbi.R R/DrawViterbiTree.R R/HFMfit.R
MD5
DESCRIPTION
man
man/HFMfit.Rd man/DrawViterbiTree.Rd man/HFMviterbi.Rd

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

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