[Ifeffit] cumulant/rdf question

[Matthew]

OK, here's my $0.02.  I've used the convolution of an exponential tail function
exp(-(r-r0)/w)    (r-r0)*w >= 0
0                        (r-r0)*r < 0

with a Gaussian.  This avoids having to have parameters go to infinity to approach a gaussian.  This function
is a little unwieldy in real space but is simple in k-space.
    mam
----- Original Message ----- 
From: "grant bunker" <bunker at iit.edu>
To: <ifeffit at millenia.cars.aps.anl.gov>
Sent: Tuesday, July 15, 2008 3:32 PM
Subject: [Ifeffit] cumulant/rdf question


> re the cumulant  <--> rdf connection
> This isn't a general solution, but it may work well for your system.
> A poisson distribution (x-x)^s Exp[-a (x-x0)] is a pretty flexible for  
> moderately skewed distributions, permitting variable C2 and C3 by  
> adjusting parameters s and a. For large s and small a the distribution  
> approaches a gaussian.
> Expressions for cumulants etc are in Yang et al, JNCS Volume 210,  
> Number 2, March 1997
> 
> have fun - gb
> 
>> matt,
>>
>> I have a problem with an exafs analysis:
>> from the exafs analysis (with feffit2.98) of the first shell of a  
>> disordered
>> system
>> I get the first three cumulants.
>> now, I wander how can reconstruct from them the radial distribution  
>> function
>> which is the best solution? I have tried with the skew-normal  
>> distribution,
>> but for the high skewness (ratio of third cumulant to sigma3)
>> values I get - that is around 2.5 - it is not well defined.
>> Do you have a suggestion?
>> Thanks,
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