comparison toolboxes/FullBNT-1.0.7/KPMstats/condgaussTrainObserved.m @ 0:e9a9cd732c1e tip

first hg version after svn

+function [mu, Sigma] = mixgaussTrainObserved(obsData, hiddenData, nstates, varargin);
+% mixgaussTrainObserved Max likelihood estimates of conditional Gaussian from raw data
+% function [mu, Sigma] = mixgaussTrainObserved(obsData, hiddenData, nstates, ...);
+%
+% Input:
+% obsData(:,i)
+% hiddenData(i)  - this is the mixture component label for example i
+% Optional arguments - same as mixgauss_Mstep
+%
+% Output:
+% mu(:,q)
+% Sigma(:,:,q) - same as mixgauss_Mstep
+
+[D numex] = size(obsData);
+Y = zeros(D, nstates);
+YY = zeros(D,D,nstates);
+YTY = zeros(nstates,1);
+w = zeros(nstates, 1);
+for q=1:nstates
+  ndx = find(hiddenData==q);
+  w(q) = length(ndx); % each data point has probability 1 of being in this cluster
+  data = obsData(:,ndx);
+  Y(:,q) = sum(data,2);
+  YY(:,:,q) = data*data';
+  YTY(q) = sum(diag(data'*data));
+end
+[mu, Sigma] = mixgauss_Mstep(w, Y, YY, YTY, varargin{:});