[SciPy-user] Iterative proportional fitting
Thu Jan 8 19:15:20 CST 2009
Could you give me one appropriate example on the way of adding the
As a example In the case of given two marginal Gaussian distributions.
I have written the corresponding bivariate Gaussian copula density , after
inverse transformation (using Sklar's theorem) to get the joint density
function their is no correlation coefficient to infer on it.
Because the joint density is not necessary a Gaussian density and I stuck
I'll try also what James suggested about maximum entropy.
Thanks for your kind help
2009/1/9 Robert Kern <firstname.lastname@example.org>
> On Thu, Jan 8, 2009 at 18:07, Dorian <email@example.com> wrote:
> > Thanks for your quick response. You are right , I've tried that, but
> > are limited only
> > to the case that the marginal distributions are uniform over the
> > zero to one.
> No, you transform your marginal distributions to uniform and also
> transform the constraints appropriately, too. You find the uniform
> copula and then apply the inverse transformations to get the original
> joint density.
> Robert Kern
> "I have come to believe that the whole world is an enigma, a harmless
> enigma that is made terrible by our own mad attempt to interpret it as
> though it had an underlying truth."
> -- Umberto Eco
> SciPy-user mailing list
-------------- next part --------------
An HTML attachment was scrubbed...
More information about the SciPy-user