fit_gaussian_mixture.m 1.8 KB
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function [StateMu,StateSqrtP,StateWeights] = fit_gaussian_mixture(X,X_weights,StateMu,StateSqrtP,StateWeights,crit,niters,check)
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% Copyright (C) 2013-2017 Dynare Team
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%
% This file is part of Dynare.
%
% Dynare is free software: you can redistribute it and/or modify
% it under the terms of the GNU General Public License as published by
% the Free Software Foundation, either version 3 of the License, or
% (at your option) any later version.
%
% Dynare is distributed in the hope that it will be useful,
% but WITHOUT ANY WARRANTY; without even the implied warranty of
% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
% GNU General Public License for more details.
%
% You should have received a copy of the GNU General Public License
% along with Dynare.  If not, see <http://www.gnu.org/licenses/>.

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[dim,Ndata] = size(X);
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M = size(StateMu,2) ;
if check                        % Ensure that covariances don't collapse
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    MIN_COVAR_SQRT = sqrt(eps);
    init_covars = StateSqrtP;
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end
eold = -Inf;
for n=1:niters
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    % Calculate posteriors based on old parameters
    [prior,likelihood,marginal,posterior] = probability3(StateMu,StateSqrtP,StateWeights,X,X_weights);
    e = sum(log(marginal));
    if (n > 1 && abs((e - eold)/eold) < crit)
        return;
    else
        eold = e;
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    end
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    new_pr = (sum(posterior,2))';
    StateWeights = new_pr/Ndata;
    StateMu = bsxfun(@rdivide,(posterior*X')',new_pr);
    for j=1:M
        diffs = bsxfun(@minus,X,StateMu(:,j));
        tpost = (1/sqrt(new_pr(j)))*sqrt(posterior(j,:));
        diffs = bsxfun(@times,diffs,tpost);
        [foo,tcov] = qr2(diffs',0);
        StateSqrtP(:,:,j) = tcov';
        if check
            if min(abs(diag(StateSqrtP(:,:,j)))) < MIN_COVAR_SQRT
                StateSqrtP(:,:,j) = init_covars(:,:,j);
            end
        end
    end
end