39 lines
1.1 KiB
Matlab
39 lines
1.1 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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%
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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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%
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%
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% part of DYNARE, copyright S. Adjemian, M. Juillard (2006)
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% Gnu Public License.
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[T,n] = size(data);
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for t = 1:T
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tt = t+offset;
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m1 = m0 + (1/tt)*(data(t,:)'-m0);
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qq = m1*m1';
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s1 = s0 + (1/tt)*(data(t,:)'*data(t,:)-qq-s0) + ((tt-1)/tt)*(m0*m0'-qq');
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m0 = m1;
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s0 = s1;
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end
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mu = m1; sigma = s1;
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offset = offset+T; |