Le us create N independent and identitcally distributed (iid) normal random vectors with zero mean and specific covariance matrix. Each vector is of size p. Let $\Sigma$ be the specific covariance matrix.
p = 20; N = 50; M = chol($\Sigma$) Matr = M' * randn(p, N)
In fact I want to know why in all references, they use
chol?. Why they don't simply write
Matr = randn(N, p) * ($\Sigma$) ? So what is the advantage of
cholcov) in this case?
I made some results, and I noticed that they significantly differ when I remove the
chol !! Even it takes more time for the computation..why??
Any help will be very appreciated!