Change distribution of a vector
I think the answer(comment) of TwinPenguins provides you a good start. You could improve this by using a Metropolis Monte Carlo approach instead of just trying again and again generating new vectors.
What you could do is:


create a new vector with length similar to yours randomly sampled from the distribution of your interest and compute KLD$_{old}$ (cf. TwinPenguins)
modify this vector and compute KLD$_{new}$.
if (KLD$_{new}$ is better than KLD$_{old}$), the new vector becomes your old vector 
else discard the changes
go back to 2, unless you reach a given target value of KLD


(Note that there may be issues with getting trapped in local minima, but search the Monte-Carlo literature and  you'll find a solution...you can always run multiple times, and then take the best result.)