[SciPy-user] CDF/PDF Stats with SciPy

Omer Khalid Omer.Khalid@cern...
Mon Jul 20 15:36:12 CDT 2009


Hi Ivo,


> The bottom line is, are you interested in:
>
> a) determining the distribution from the actual data without bothering to
> know the exact formula and drawing conclusions (that is find moments,
> probabilities,etc) from it (that is what I normally do)


Yes, I am interested in this.



> b) try to determine what distribution your data fits the best (i.e., is it
> normal, ricean, rayleigh, nakagammi, etc)


This is partially true..

I think I should have explained more of my research question. My program is
generating a real number variate X for every success. I keep on storing X
for each success cycle of my program and once the sample list is size 1000;
then I would like to use that sample space to determine the probability for
every next X and again store it until the sample space reaches 1000.

I am not really concerned with the distribution type of my sample space, so
i thought (may be out of ignorance) that I first must determine the
distribution type using the fit function and then get the mean/std. Once I
have mean/std, then i get CDF probability for every next X and store it my
sample list replace the previous once.

Basically, I want to get a probability for every X in my program cycle till
the next sample space reaches 1000, and keeps on doing it. This way I am
assuming my algorithm will learn to improve.

But I could not figure out the proper python code  yet for this....

Thanks,
Omer
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