%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% Compute log-likelihood in time domain for SSM objects% % INPUT% % - in, a vector of input signals aos% - out, a vector of output data aos% - parvals, a vector with parameters values% - parnames, a cell array with parameters names% - model, an ssm model% - inNames, A cell-array of input port names corresponding to the% different input AOs% - outNames, A cell-array of output ports to return% - Noise, a vector of noise aos% - cutbefore, followed by the data samples to cut at the starting of the% data series% - cutafter, followed by the data samples to cut at the ending of the% data series%% L Ferraioli 10-10-2010%% $Id: loglikelihood_ssm_td.m,v 1.1 2011/03/15 16:19:20 miquel Exp $%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%function loglk = loglikelihood_ssm_td(xp,in,out,parnames,model,inNames,outNames,Noise,varargin)% xn,in,out,noise,model,params,inNames,outNames cutbefore = []; cutafter = []; if ~isempty(varargin) for j=1:length(varargin) if strcmp(varargin{j},'cutbefore') cutbefore = varargin{j+1}; end if strcmp(varargin{j},'cutafter') cutafter = varargin{j+1}; end end end xp = double(xp); fs = out(1).fs; % set parameters in the model evalm = model.setParameters(plist('names',parnames,'values',xp)); evalm.keepParameters(); evalm.modifyTimeStep(plist('newtimestep',1/fs)); %%% get expected outputs plsym = plist('AOS VARIABLE NAMES',inNames,... 'RETURN OUTPUTS',outNames,... 'AOS',in); eo = simulate(evalm,plsym);% %%% get expected noise% plsym = plist('AOS VARIABLE NAMES',inNoiseNames,...% 'RETURN OUTPUTS',outNames,...% 'AOS',inNoise);% eon = simulate(evalm,plsym); %%% get measurement noise res = out-eo; loglk = utils.math.loglikehood_td(res,Noise,'cutbefore',cutbefore,'cutafter',cutafter);end