Yes, I think we would be interested in confidence intervals, but I think the algorithm should be very well standard/cited, even if it's not the best/most modern. @WarrenWeckesser and I had planned to work on confidence intervals for the test statistics returned by our statistical tests <https://docs.scipy.org/doc/scipy/reference/stats.html#statistical-tests>. On Mon, Jun 8, 2020 at 2:11 AM Romain Jacob <jacobr@ethz.ch> wrote:
Hello everyone,
I have been working for some time on the implementation of non-parametric methods to compute confidence intervals for percentiles. There are some very interesting results in the literature (see e.g. a nice pitch in [1]) which I think it would be great to add to SciPy to make them more readily available. It also seems to be rather in line with "recent" discussions of the roadmap for scipy.stats [2].
I would be interested in contributing this. What do you think?
Cheers, -- Romain
[1] https://ieeexplore.ieee.org/document/6841797 [2] https://github.com/scipy/scipy/issues/10577 -- Romain Jacob Postdoctoral Researcher ETH Zurich - Computer Engineering and Networks Laboratory www.romainjacob.net @RJacobPartner <https://twitter.com/RJacobPartner> Gloriastrasse 35, ETZ G75 8092 Zurich +41 7 68 16 88 22 _______________________________________________ SciPy-Dev mailing list SciPy-Dev@python.org https://mail.python.org/mailman/listinfo/scipy-dev
-- Matt Haberland Assistant Professor BioResource and Agricultural Engineering 08A-3K, Cal Poly