estimation stable distribution parameters
Hi, This just repetition of my mail, so please apologize me if you receive it twice. I am wondering whether anyone of you already implemented in R or S+ the methods of estimation the parameters of stable distribution (especially the iid case). If there is, i will be happy to get the copy of the codes. Some R-users referred me to the package stable (thanks M. Maechler and B. Pikounis), but i think it does not give the answer to my question. Probably i can use function stablereg in the package, but after read the explanation of the function, i am totally confused with the result reported. Simply applying what they shown in the example in the help for this function, for example check for the line after #Stable model with loc(ation)=loc.h(b0+b1*day) i got result of skewness estimate as -2.05 which is an incorrect thing (? i am not sure, probably my interpretation is wrong)
It is correct for the parametrisation used.
It looks like they implemented the method of estimation for regression model based on approximate / conditional maximum likelihood (I didn't check their codes yet, and also until now i can not get the referred paper). I intended to see the accuracy of the other estimation procedures e.g. the method of quantile's of McCulloch or the method based on ECF. Some colleagues referring me to Xplore, where Weron has implement the methods using the languange Xplore, however it is inaccessible for public.
It uses exact MLE with numerical precision set by the integration (user specified). The methods to which you refer are all obsolete. Jim
Please let me know if any body has any clues to my question. Otherwise, i have to start writing my own codes Regards Dedi t
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