MATLAB: Difference between mvnrnd(,sigma) and randn()*chol(sigma)

cholesky decompositionmultivariate normal random numbers

I would like to create correlated multivariate normal random numbers. It is my understanding that this can either be done using the Statistic Toolbox function mvrnd or by using randn with a Cholesky decomposition of the covariance matrix (sigma).
rng('default')
sigma = [1 .5;0.5 1];
R = mvnrnd(zeros(100,2),sigma);
R2 = randn(100,2)*chol(sigma);
corrcoef(R)
corrcoef(R2)
However, above code gives me different random numbers (although they do exhibit the desired correlation). Why is this the case? Is their a difference between using mvnrnd() and randn()*chol()?
Best regards, Florian

Best Answer

Did you forget to reset the random number generator between the two calls? mvnrnd and randn draw random values from the same stream.
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