spm_vb_init_volume.m
8a186cd82567master

spm_vb_init_volume.m
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			function [slice] = spm_vb_init_volume(X,p)
			% Initialise generic aspects of slice structure for VB-GLM-AR models
			% FORMAT [slice] = spm_vb_init_volume(X,p)
			%
			% X - design matrix
			% p - AR model order
			%
			% slice - data structure (see spm_vb_glmar)
			%__________________________________________________________________________
			% Copyright (C) 2005-2014 Wellcome Trust Centre for Neuroimaging

			% Will Penny and Nelson Trujillo-Barreto
			% $Id: spm_vb_init_volume.m 6079 2014-06-30 18:25:37Z spm $

			% disp('Initialising volume');
			% disp(' ');


			slice.X = X;
			slice.p = p;
			slice.k = size(X,2);

			T = size(X,1);
			slice.T = T;

			slice.XT = X';
			slice.XTX = slice.XT*X;

			for t=p+1:T
			slice.dX(:,:,t-p) = X(t-1:-1:t-p,:);
			end

			[ux,dx,vx] = svd(X);
			if size(dx,2) > 1
			ddx=diag(dx);
			else
			% design matrix with a single column
			ddx = dx;
			end
			svd_tol = max(ddx)epsslice.k;
			rank_X = sum(ddx > svd_tol);
			ddxm = diag(ones(rank_X,1)./ddx(1:rank_X));
			ddxm2 = diag(ones(rank_X,1)./(ddx(1:rank_X).^2));
			slice.Xp = vx(:,1:rank_X)ddxmux(:,1:rank_X)';
			slice.X2 = vx(:,1:rank_X)ddxm2vx(:,1:rank_X)';

			k = slice.k;
			% Get lagged input covariances for updates
			slice.I.Gx = slice.X(p+1:T,:)'*slice.X(p+1:T,:);
			slice.I.xtx = slice.X(p+1:T,:)'*slice.X(p+1:T,:);
			for ki=1:k
			for kj=1:k
			dXki = squeeze(slice.dX(:,ki,:));
			dXkj = squeeze(slice.dX(:,kj,:));
			if slice.p==1
			% singleton dimension already transposed
			dXki = dXki';
			dXkj = dXkj';
			end
			Stmp = dXki*dXkj';
			slice.I.S((kj-1)*k+ki,:) = Stmp(:)';

			R1tmp = dXkj*slice.X(p+1:T,ki);
			slice.I.R1((kj-1)*k+ki,:) = R1tmp';
			end
			end