[SciPy-user] Iterative proportional fitting

Dorian wizzard028wise@gmail....
Thu Jan 8 21:04:00 CST 2009

Hi  Kern ,  James

I look at closely the "Maximum entropy method " and "NORTA method" , they
correspond exactly
to what I'm looking for to start thinking deeply about the problem of
approaching likely the density
function which will  correspond to a given marginal densities functions.

Thanks  a lot ,


P.S  to Kern :  As English isn't my language , I speak French ,  I'm still
learning English.  I didn't understand at the beginning the meaning of
"butt" , I was really confused by the definition given by google. Then I
google the all sentence " talk out of my butt" and I understood what you
meant [?]

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

> On Thu, Jan 8, 2009 at 19:15, Dorian <wizzard028wise@gmail.com> wrote:
> > Could you give me one appropriate  example on the way of adding the
> > constraints?
> >
> > 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
> > there .
> Hmm, I could be talking out of my butt, here. The last time I looked
> at something like this was years ago, and my problem was just
> generating random numbers, not trying to derive density functions. I
> was looking at the NORTA (NORmal To Anything) method. It might be
> possible to derive a method for estimating a joint density using a
> similar approach.
> What information do you have? Just the marginal densities? Can you
> describe your problem at a higher level?
> --
> 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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