[MATH] - Truncated Normal Distribution
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? Cheers, Marko
Re: [MATH] - Truncated Normal Distribution
I'd be happy to contribute. On Sun, Nov 29, 2020, 11:22 PM Marko Malenic wrote: > 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? > > Cheers, > Marko >
Re: [MATH] - Truncated Normal Distribution
Hello. Le lun. 30 nov. 2020 à 08:22, Marko Malenic 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
Re: [MATH] - Truncated Normal Distribution
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 wrote: > Hello. > > Le lun. 30 nov. 2020 à 08:22, Marko Malenic 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 > >
Re: [MATH] - Truncated Normal Distribution
Hello. Le mar. 1 déc. 2020 à 01:42, Marko Malenic a écrit : > > 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. Some of the implemented distributions use the inverse transform. It's fine and sane to not do everything at once. ;-) Indeed, if you implement another sampler, it must go into the "sampling" module of "Commons RNG", reusing functionality already implemented there (if applicable). Regards, Gilles > [...] - To unsubscribe, e-mail: dev-unsubscr...@commons.apache.org For additional commands, e-mail: dev-h...@commons.apache.org
Re: [MATH] - Truncated Normal Distribution
Awesome. Should I submit a jira ticket for this? On Tue, Dec 1, 2020 at 12:11 PM Gilles Sadowski wrote: > Hello. > > Le mar. 1 déc. 2020 à 01:42, Marko Malenic a écrit : > > > > 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. > > Some of the implemented distributions use the inverse transform. > It's fine and sane to not do everything at once. ;-) > > Indeed, if you implement another sampler, it must go into the > "sampling" module of "Commons RNG", reusing functionality > already implemented there (if applicable). > > Regards, > Gilles > > > [...] > > - > To unsubscribe, e-mail: dev-unsubscr...@commons.apache.org > For additional commands, e-mail: dev-h...@commons.apache.org > >
Re: [MATH] - Truncated Normal Distribution
Hello. Le mar. 1 déc. 2020 à 06:02, Marko Malenic a écrit : > > Awesome. > > Should I submit a jira ticket for this? Yes. https://issues.apache.org/jira/browse/STATISTICS Regards, Gilles > > On Tue, Dec 1, 2020 at 12:11 PM Gilles Sadowski > wrote: > > > Hello. > > > > Le mar. 1 déc. 2020 à 01:42, Marko Malenic a écrit : > > > > > > 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. > > > > Some of the implemented distributions use the inverse transform. > > It's fine and sane to not do everything at once. ;-) > > > > Indeed, if you implement another sampler, it must go into the > > "sampling" module of "Commons RNG", reusing functionality > > already implemented there (if applicable). > > > > Regards, > > Gilles > > > > > [...] - To unsubscribe, e-mail: dev-unsubscr...@commons.apache.org For additional commands, e-mail: dev-h...@commons.apache.org