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.

AuthorHenrik Failmezger, Achim Tresch
Date of publication2016-09-19 01:45:39
MaintainerHenrik Failmezger <Henrik.Failmezger@googlemail.com>
LicenseGPL (>= 2)
Version1.0.3

View on CRAN

Files in this package

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

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

All documentation is copyright its authors; we didn't write any of that.