https://github.com/OHBA-analysis/HMM-MAR
Tip revision: 7e3a60e3f2c8dd23ed279988cd92aaa98c622331 authored by Diego Vidaurre on 20 August 2022, 08:47:06 UTC
Cosmetic changes
Cosmetic changes
Tip revision: 7e3a60e
episodichmm.m
function [ehmm, Gamma, GammaInit, crithist] = episodichmm (data,T,options)
%
% Train Hidden Markov Model using using Variational Framework
%
% INPUTS
% data observations; either a struct with X (time series)
% or a matrix containing the time series,
% or a list of file names
% T length of series
% options structure with the training options - see documentation in
% https://github.com/OHBA-analysis/HMM-MAR/wiki
%
% OUTPUTS
% ehmm estimated ehmm model
% Gamma estimated p(state | data)
% GammaInit The HMM-initialised Gamma that is fed to the ehmm inference
%
% Author: Diego Vidaurre,
% CFIN, Aarhus University / OHBA, University of Oxford (2021)
options.episodic = true;
[ehmm, Gamma, ~, ~, GammaInit, ~, crithist] = hmmmar(data,T,options);
end