function [x]=sampgauss(m,C,N)%%  x=SAMPGAUSS(m,C,N)%%  samples N-times from an multi-dimensional gaussian distribution %  with covariance matrix C and mean m. Dimensionality is implied%  in the mean vector%%  e.g: C=[1 .7;0.7 1];%       m=[0;0];%       x=sampgauss(m,C,300);%(see e.g. B.D. Ripley, Stochastic Simulation, Wiley, 1987, pp. 98--99)%m=m(:);r=size(C,1);if size(C,2)~= r  error('Wrong specification calling normal')end% find cholesky decomposition of A[L,p]=chol(C);% generate r  independent N(0,1) random numbersz=randn(r,N);x=m(:,ones(N,1))+L*z;