Hi, I'm a bit new to all this stuff, so bear with me while I ask some questions :)
There's a few ways to do this. In terms of number generation, there's a few algorithms, some of which at described at: https://en.wikipedia.org/wiki/Truncated_normal_distribution#Computational_methods Any preferences on how to generate the numbers? I noticed sampling is split off to commons rng. Should another sampler be added, depending on the algorithm? Or maybe just using inverse transform sampling would be okay. Let me know your thoughts, Marko On Tue, Dec 1, 2020 at 12:42 AM Gilles Sadowski <gillese...@gmail.com> wrote: > Hello. > > Le lun. 30 nov. 2020 à 08:22, Marko Malenic <mmalen...@gmail.com> a écrit > : > > > > Hi all, > > > > I'm interested in contributing here, and have been wanting to implement > and > > add a truncated normal distribution. Would anyone be interested in this? > > Contributions welcome. ;-) > > This would be an addition for the new "Commons Statistics" component: > http://commons.apache.org/proper/commons-statistics/ > in module "distribution": > > https://gitbox.apache.org/repos/asf?p=commons-statistics.git;a=tree;f=commons-statistics-distribution > > Thanks for your interest, > Gilles > > --------------------------------------------------------------------- > To unsubscribe, e-mail: dev-unsubscr...@commons.apache.org > For additional commands, e-mail: dev-h...@commons.apache.org > >
