Re: Skew-t distribution
Ralf Gommers <[email protected]> Wed, 26 Jul 2023 00:08:17 +0200
| Newsgroups | gmane.comp.python.scientific.devel |
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| Message-ID | <CABL7CQiJDY0L6PBznMq4tfwHmgF1VE43GFUQwy59hrP1mvLLGQ@mail.gmail.com> |
On Tue, Jul 25, 2023 at 5:05 AM Albert Steppi <[email protected]> wrote: > +1, it seems like it would be a good addition. > > On Mon, Jul 24, 2023 at 2:28 AM JohnWT <[email protected]> wrote: > >> I was reading through the development workflow page, and it said if I was >> trying to add any new functions I should email this mailing list. >> >> Link to PR: https://github.com/scipy/scipy/pull/18948 >> >> Link to issue: https://github.com/scipy/scipy/issues/18947 >> >> Motivation for new distribution: The Jones and Faddy skew-t distribution >> provides a good fit to heavy tailed and skewed data. It has several >> applications, and is a relatively tractable distribution which makes it >> quite easy to use. >> > Thanks for the proposal John. This looks like a good fit, and the paper on this distribution easily has enough citations to show that it's of interest. > >> Please let me know if there is anything else I need to do - this is the >> first time I've tried to contribute! >> > I think you've done it all - you've gotten multiple thumbs-up's, and your PR already seems to be in pretty good shape. So getting that merged is all that's left to do here I think. Cheers, Ralf _______________________________________________ SciPy-Dev mailing list -- [email protected] To unsubscribe send an email to [email protected] https://mail.python.org/mailman3/lists/scipy-dev.python.org/ Member address: [email protected]