Re: [Quantlib-users] copulas library proposal

[Ferdinando M. Ametrano-3]

Hi Marek

> Copulas might be useful as a part of math library and for some models
>  I attached proposal for:
>  ql/math/copulas/[...]

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.

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 ;-)

One question: you contributed bidimensional copulas. Is there an
efficient standard approach how to generalize to arbitrary dimensions?

>  Sorry for inconveniance, If I put this in wrong place, I'm quite new
>  to sourceforge and quantlib.
using the quantlib-dev mailing list would have been better, but I am
aware that the line between users and developers is blurred when it
comes to a C++ library.
You might want to reply only to the quantlib-dev address for further
discussions in this thread.

Thank you again

ciao -- Nando

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[Marek2]

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