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offset is updated after each call. 

Documentation of the function.

git-svn-id: https://www.dynare.org/svn/dynare/dynare_v4@1284 ac1d8469-bf42-47a9-8791-bf33cf982152
time-shift
adjemian 2007-05-19 16:50:20 +00:00
parent 6e4e16a378
commit 243484b387
1 changed files with 29 additions and 18 deletions
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47
matlab/recursive_moments.m
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@ -1,28 +1,39 @@
function [mu,sigma] = recursive_moments(m0,s0,data,offset) function [mu,sigma,offset] = recursive_moments(m0,s0,data,offset)
% stephane.adjemian@cepremap.cnrs.fr [02-03-2005] % Recursive estimation of order one and two moments (expectation and
% covariance matrix).
%
% INPUTS
% o m0 [double] (n*1) vector, the prior expectation.
% o s0 [double] (n*n) matrix, the prior covariance matrix.
% o data [double] (T*n) matrix.
% o offset [integer] scalar, number of observation previously
% used to compute m0 and s0.
%
% OUTPUTS
% o mu [double] (n*1) vector, the posterior expectation.
% o sigma [double] (n*n) matrix, the posterior covariance matrix.
% o offset [integer] = offset + T.
% %
% m0 :: the initial mean, assumed to be a n*1 vector. % ALGORITHM
% s0 :: the initial variance, assumed to be a n*n matrix. % None.
% data :: T*n matrix.
% %
% mu :: the sample mean, a n*1 vector. % SPECIAL REQUIREMENTS
% sigma :: the sample covariance matrix, a n*n matrix. % None.
% %
% --> TODO: dll %
T = size(data,1); % part of DYNARE, copyright S. Adjemian, M. Juillard (2006)
n = size(data,2); % Gnu Public License.
[T,n] = size(data);
for t = 1:T for t = 1:T
tt = t+offset; tt = t+offset;
m1 = m0 + (1/tt)*(data(t,:)'-m0); m1 = m0 + (1/tt)*(data(t,:)'-m0);
s1 = s0 + (1/tt)*(data(t,:)'*data(t,:)-m1*m1'-s0) + ((tt-1)/tt)*(m0*m0'-m1*m1'); qq = m1*m1';
s1 = s0 + (1/tt)*(data(t,:)'*data(t,:)-qq-s0) + ((tt-1)/tt)*(m0*m0'-qq');
m0 = m1; m0 = m1;
s0 = s1; s0 = s1;
end end
mu = m1; mu = m1; sigma = s1;
sigma = s1; offset = offset+T;