Ted: No, I mean with the discrete inverse cdf. But anyway. Thanks for clarifying the points.
Phil, if you're not convinced, I'll be happy to provide a patch-draft/prototype of code so you can see exactly what I mean? If we were to put a generator in the distributions (for supporting the specialised generators), should this method then just be parameterised by a RandomGenerator? Or what would be a proper approach? 2009/10/27 Ted Dunning <ted.dunn...@gmail.com>: > That was Phil. (not that it matters) > > +1 for the idea of a default generator for all distributions that define a > cumulative density. > > +1 as well for specialized implementations where possible that over-ride the > default generator even if it exists. > > I can't imagine much dispute on either of these points because they satisfy > the general principle of doing the best we can for all cases as well as for > special cases. > > I also completely agree with Mikkel with not understanding why the > generation of deviates is separated from the distribution. > > On Mon, Oct 26, 2009 at 5:11 PM, Mikkel Meyer Andersen <m...@mikl.dk> wrote: > >> Ted, sorry hadn't seen your e-mail before sending mine. >> >> Yes, I agree in you point of having specialised good algorithms. But >> in lack of such methods, I'd prefer being able to have a general >> method, although it might be bad compared to a specialised one. >> >> 2009/10/27 Phil Steitz <phil.ste...@gmail.com>: >> > Thanks. That's what I was missing. I would still rather see the >> > implementations in the random package and for common distributions, >> > e.g. Poisson, pick a method that is well-suited for the distribution. >> > --------------------------------------------------------------------- To unsubscribe, e-mail: dev-unsubscr...@commons.apache.org For additional commands, e-mail: dev-h...@commons.apache.org
