New Post: Multivariable Random Number Generator

Thanks Christoph!

I was giving a look at the documentation, but I didn't fully understand how to use it. There you say:

The distribution is parameterized by a mean matrix (M), a covariance matrix for the rows (V) and a covariance matrix for the columns (K). If the dimension of M is d-by-m then V is d-by-d and K is m-by-m.

But now I have a question. Let's say that I have the following correlation matrix for 3 different variables:

       v1  v2  v3
v1  [ 1, 0.6, 0.3 ]
v2  [ 0.6, 1, 0.5 ]
v3  [ 0.3, 0.5, 1 ]

You are saying that in order to use the Matrix Distribution, should I have a 3 x 3 M, a 3 x 3 K and a 3 x 3 V. The M is fine for me, but I just don't understand how to work with V and K, as I was expecting a 1 x 3 and 3 x 1 matrices for row and column covariances...

Thanks,
Rafael