📄 spm_mar_conn.m.svn-base
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function [psig,chi2] = spm_mar_conn (mar,conn)
% Test for significance of connections
% FORMAT [psig,chi2] = spm_mar_conn (mar,conn)
%
% mar MAR data structure (see spm_mar.m)
% conn conn(i,j)=1 if we are testing significance
% of connection from time series i to time
% series j - zero otherwise
%
% psig significance of connection
% chi2 associated Chi^2 value
%
%___________________________________________________________________________
% Copyright (C) 2007 Wellcome Department of Imaging Neuroscience
% Will Penny
% $Id$
pmat=eye(mar.p);
for i=1:mar.p,
C(i).mat=kron(pmat(:,i),conn);
end
C_con=[];
for i=1:mar.p,
C_con=[C_con, C(i).mat(:)];
end
w_hat=mar.wmean(:);
% Pick off all AR coefficients for that connection
% (ie. at all lags)
c_tilde=C_con'*w_hat;
% Get corresponding part of AR coeff covariance matrix
Sigma_tilde=C_con'*mar.w_cov*C_con;
chi2=c_tilde'*inv(Sigma_tilde)*c_tilde;
psig=1-chi2cdf(chi2,mar.p);
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