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VARHMMBOX, version 1.1, Iead Rezek, Oxford University, MAR 2002 Matlab toolbox for Hidden Markov Mo

VARHMMBOX, version 1.1, Iead Rezek, Oxford University, MAR 2002
Matlab toolbox for Hidden Markov Models

(Adapted from Machine Learning Toolbox
Version 1.0  01-Apr-96
Copyright (c) by Zoubin Ghahramani, University of Toronto)

The software uses some NETLAB routines 
(see http://neural-server.aston.ac.uk/netlab/index.html)
so you'll need to have NETLAB on your search path

See the file VERSION for what's new in this version.

The following observation models have so far been implemented:
Gaussian, Gaussian with common covariances, Likelihood, AR.

DEMONSTRATIONS:

demgausshmm.m       uses Gaussian observation model 
demgausshmm_traj.m  uses Gaussian observation model on a trajectory
demgausshmm_back.m  Gaussian observation model using backwards 
                    compatibility functions
dempoissonhmm.m     uses Poisson observation model on RR intervals
demlike.m        the time series values are themselves likelihoods
sleepdemo           Gaussian observation model on Sleep EEG Features

ROUTINES:

Read the file Contents.m


To extend the HMM to different observation models add the required
code into obsinit, obslike and obsupdate.

DATA:

Read the file DATA-STRUCTURE.