In matlab it is easy to generate a normally distributed random vector with a mean and a standard deviation. From the help randn:
Generate values from a normal distribution with mean 1 and standard deviation 2. r = 1 + 2.*randn(100,1);
Now I have a covariance matrix C and I want to generate N(0,C).
But how could I do this?
From the randn help: Generate values from a bivariate normal distribution with specified mean vector and covariance matrix. mu = [1 2]; Sigma = [1 .5; .5 2]; R = chol(Sigma); z = repmat(mu,100,1) + randn(100,2)*R;
But I don't know exactly what they are doing here.