On 30.07.2010 18:51, Paul A. Bristow wrote:
-----Original Message----- From: boost-users-bounces@lists.boost.org [mailto:boost-users-bounces@lists.boost.org] On Behalf Of Thomas Mang Sent: Friday, July 30, 2010 4:29 PM To: boost-users@lists.boost.org Subject: [Boost-users] [distributions]: Inverse Gamma
Hi,
any plans of implementing the inverse gamma distribution as part of the distributions library ?
This looks possible - but I'm curious about applications - you obviously have one, but Wikipedia doesn't mention any
http://en.wikipedia.org/wiki/Inverse-gamma_distribution
But you obviously have one ;-)
Yes I truly have one ;) The inverse gamma distribution and its special case, the scaled inverse chi-square distribution, is the conjugate prior to the normal distribution variance parameter in Bayesian statistics. Pretty much as uncommon and unheard of as it is outside Bayes world [to the best of my knowledge], it's very much central to Bayesian stats and appears in every textbook right after the introduction chapter ;) http://en.wikipedia.org/wiki/Scaled_inverse_chi-square_distribution http://en.wikipedia.org/wiki/Conjugate_prior Hence I wonder it has not been requested so far - but being a Bayesian C++ / booster I definitely want / need it :). @John: Yes it is a transformation deviate of the gamma, and an easy so. And it should be fairly easy to implement IMHO. Is contribution on my side expected (can be done just notice I am a [heavy !] user of the stats library only, not familiar with code / numerical stability issues).
What about multivariate (in particular the multivariate normal and t distributions and Wishart and Dirichlet ) ?
A previous offer to do some multivariate distributions seems have fizzled out - perhaps because it is *much* more difficult, particularly with the templated and 'policied ' (to control the troublesome parameter cases) structure used for the Boost.Math library. There may be no analytic expressions for some like inverse and CDF.
So some strong motivation and support would be needed to embarge on this.
Paul
I think the multivariate normal is fairly obvious, use for the others equally arises in Bayesian statistics. But I understand that everything is much more complicated. What about 'vegetarian' versions offering say only the pdf (that is needed a lot. Personally I have never had the need for CDFs / inverse CDFs as these are truly a big mess. But the pdf - yes would be cool). best, Thomas
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