Hi Ferdinando
>>thanks for the contribution, I've just added it in the trunk code base.
>>I've pruned redundant inclusions, move inclusion to cpp file when
>>possible, expanded error messages to be more informative, and avoided
>>instantiating objects in the GaussianCopula::operator() method since
>>they could be instantiated once for all in the constructor.
Thanks for improvements, now code looks and works better.
>>It would be nice if you would contribute a unit test which reproduces
>>known tabulated values. This way I could have checked that I didn't
>>introduce any error ;-)
Unfortunately, I don't have any source for copulas values, neither in
printed
form nor by commercal software packages, I only find free library for R.
I check code and I don't find any error. I think accuracy is as good as
accuracy
of exp and other standard functions ;)
>>One question: you contributed bidimensional copulas. Is there an
>>efficient standard approach how to generalize to arbitrary dimensions?
As far I know in general there is no easy way to generalize arbitrary copula
to n-dimension, but some special families like elliptical it's quite easy.
For example for gaussian copula in place of bivariate_normal place
multivariate_normal, but for the time being in quantlib there is no
multivariate
normal except bivariate of course ;) Additional problem is interface,
for more than n-dimenisional copulas I suggest to use vector of n-variables.
It could be interesting to develop, but I think multivariate distributions
should be done first.
Best Regards
Marek
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