52 lines
1.6 KiB
Matlab
52 lines
1.6 KiB
Matlab
function [mu,sigma,offset] = recursive_moments(m0,s0,data,offset)
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% Recursive estimation of order one and two moments (expectation and
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% covariance matrix).
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%
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% INPUTS
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% o m0 [double] (n*1) vector, the prior expectation.
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% o s0 [double] (n*n) matrix, the prior covariance matrix.
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% o data [double] (T*n) matrix.
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% o offset [integer] scalar, number of observation previously
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% used to compute m0 and s0.
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% OUTPUTS
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% o mu [double] (n*1) vector, the posterior expectation.
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% o sigma [double] (n*n) matrix, the posterior covariance matrix.
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% o offset [integer] = offset + T.
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%
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% ALGORITHM
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% None.
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%
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% SPECIAL REQUIREMENTS
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% None.
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% Copyright © 2006-2017 Dynare Team
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%
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% This file is part of Dynare.
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%
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% Dynare is free software: you can redistribute it and/or modify
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% it under the terms of the GNU General Public License as published by
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% the Free Software Foundation, either version 3 of the License, or
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% (at your option) any later version.
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%
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% Dynare is distributed in the hope that it will be useful,
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% but WITHOUT ANY WARRANTY; without even the implied warranty of
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% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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% GNU General Public License for more details.
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%
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% You should have received a copy of the GNU General Public License
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% along with Dynare. If not, see <https://www.gnu.org/licenses/>.
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[T,~] = size(data);
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for t = 1:T
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tt = t+offset;
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m1 = m0 + (data(t,:)'-m0)/tt;
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qq = m1*m1';
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s1 = s0 + ( (data(t,:)'*data(t,:)-qq-s0) + (tt-1)*(m0*m0'-qq') )/tt;
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m0 = m1;
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s0 = s1;
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end
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mu = m1;
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sigma = s1;
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offset = offset+T; |