> > I've spent quite some time on MATH-753 [1], and I think I now have a > > satisfactory solution. > > The problem was to overcome the overflows which arise when computing > > the density of the Gamma distribution for large values of the argument > > and/or the scale parameter. > > > > As I initially feared, what was proposed in the JIRA ticket leads to > > high floating point errors. I adapted a method proposed in BOOST [2] > > with acceptable errors. Meanwhile, I've also managed to improve the > > accuracy of the computation of the density for the range of parameters > > where the previous implementation was already working: in this range, > > the accuracy *was* about 300 ulps, and is now 1-2 ulps! I think this > > improvement is worth implementing. > > > > The downside is that I need to expose the Lanczos implementation > > internally used by o.a.c.m3.special.Gamma. This approximation is so > > standard that I don't see it as a problem. I don't think that it > > reveals too much of the Gamma internals, since the javadoc of > > Gamma.logGamma states that it uses this approximation. So what I > > propose is the addition of two methods in Gamma: > > double getLanczosG(): returns the g constant > > double getLanczos(double): returns the value of the Lanczos sum.
Is that something useful only inside the "Gamma" class? If not, maybe that it can become a stand-alone class, or a method in one of the "utility" classes (in package "util"). > > > > If you do not like this option, I can copy/paste the Lanczos > > approximation in the GammaDistribution class. I'm adverse to the > > latter option, as it leads to code duplication. No "copy/paste" for me, thank you. :-) Best, Gilles --------------------------------------------------------------------- To unsubscribe, e-mail: dev-unsubscr...@commons.apache.org For additional commands, e-mail: dev-h...@commons.apache.org
