--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/m-toolbox/classes/+utils/@math/loglikelihood_ssm_td.m	Wed Nov 23 19:22:13 2011 +0100
@@ -0,0 +1,68 @@
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+%
+% 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
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