[SciPy-user] Iterative proportional fitting

Dorian wizzard028wise@gmail....
Thu Jan 8 18:07:38 CST 2009


Thanks for your quick response. You are right , I've tried that, but copula
are limited only
to the case that the marginal distributions are uniform over  the interval
zero to one.

As I read  from literature  IPF method is more general and can be applied
also with marginal
distributions, not limited to the interval zero to one .

Thanks again,

Dorian







2009/1/9 Robert Kern <robert.kern@gmail.com>

> On Thu, Jan 8, 2009 at 17:06, Dorian <wizzard028wise@gmail.com> wrote:
> > Hi all,
> > I have some marginal functions densities and I'm looking to the good way
> to
> > find their join density function.
>
> There are potentially an infinite number of such joint density
> functions that have the same marginal densities. Adding some
> constraints, like a correlation between two variables, helps, but it's
> still an ill-defined problem.
>
> > I would want to know if there is any  package or script in Scipy  for
> > iterative proportional fitting (IPF) .
> > Or any web link to help  me start.
>
> No, there is nothing in scipy for this. I think IPF applies more to
> data than to distributions, per se. Estimating a joint distribution
> from marginal distribution is usually called a copula, in my
> experience.
>
> http://en.wikipedia.org/wiki/Copula_(statistics)<http://en.wikipedia.org/wiki/Copula_%28statistics%29>
>
> --
> 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
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