Question: If I give you the mean vector and the covariance matrix of a multivariate gaussian distribution (call it G1), is there a way to find a lognormal distribution which mimics the shape of G1?
I mean, such a lognormal distribution has an underlying multivariate gaussian distribution (call it G2). Is there an analytic solution, such that the mean and covariance of G1 can be converted to those of G2?
Thank you very much indeed in advance!
PS. Of course, multivariate gaussian and lognormal are different, I just try to see if it is possible find a lognormal which mimic the multivariate gaussian as much as possible.
A relevant question is below too,
but wanted to have some ideas on stackexchange too.