[SciPy-Dev] Adding non-parametric methods to scipy.stats

Fri Jun 12 11:29:42 EDT 2020

On Fri, Jun 12, 2020 at 1:58 AM Romain Jacob <jacobr at ethz.ch> wrote:

> On 11/06/2020 20:54, Warren Weckesser wrote:
>
> On 6/11/20, josef.pktd at gmail.com <josef.pktd at gmail.com> <josef.pktd at gmail.com> wrote:
>
> I think it would make a good and useful addition and fit into scipy.stats.
> There are no pure confint functions yet, AFAIR.
>
> I agree with Josef and Matt, this looks like it would be a nice
> addition to SciPy.  At the moment, I'm not sure what the API should
> look like.  Romain, is the work that you've already done available
> online somewhere?
>
> Warren
>
> Yes, I have some functional implementation available here:
> https://github.com/TriScale-Anon/triscale/blob/master/helpers.py#L397
>

An implementation detail:
binom has cdf and ppf functions
My guess, not verified, is that we can just use binom.interval

(at least I used those for similar cases)

Josef

> There is quite some work to be done on formatting and documentation to
> comply with the SciPy standards, but functionally it's already there (and
> as you'll see, the method is quite simple).
>
> Cheers,
> --
> Romain
>
> I recently wrote a function for the confidence interval for the median,
> mainly because I ran into the formulas that were easy to code.
> related open issue: how do we get confidence intervals for QQ-plot.
>
> aside: I don't like "percent", I prefer quantiles in [0, 1]. See discussion
> a while ago in numpy.
>
> Josef
>
>
> On Thu, Jun 11, 2020 at 1:01 PM Matt Haberland <mhaberla at calpoly.edu> <mhaberla at calpoly.edu>
> wrote:
>
>
> OK, we should let our statistics experts weigh in on this. (I'm not
> actually one of them.)
>
> On Wed, Jun 10, 2020 at 10:46 PM Romain Jacob <jacobr at ethz.ch> <jacobr at ethz.ch> wrote:
>
>
> I think a dedicated function makes more sense. This function takes as
> input an array, a percentile and a confidence level, and returns the
> corresponding one-sided confidence intervals.
>
> I quickly looked at the list of existing functions in scipy.stats but
> did
> not see any function in "summary statistics" that does similar things. So
> I
> would go for a new function.
> On 10/06/2020 20:38, Matt Haberland wrote:
>
> Where do you envision this living in SciPy? In its own function, or
> added
> functionality to other functions e.g. scipy.stats.percentileofscore<https://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.percentileofscore.html#scipy.stats.percentileofscore> <https://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.percentileofscore.html#scipy.stats.percentileofscore>
> ?
>
> On Tue, Jun 9, 2020 at 11:12 PM Romain Jacob <jacobr at ethz.ch> <jacobr at ethz.ch> wrote:
>
>
> On 09/06/2020 20:18, Matt Haberland wrote:
>
> 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.
>
> Yes definitely! We did not invented the method I am referring to, it a
> long-known approach (first proposed by Thompson in 1936 [1], extended
> later
> and commonly found in textbooks, eg [2,3]). This method is very simple,
> quite powerful, yet it has been largely overlooked in many scientific
> fields. I found no available implementation to facilitate its use (at
> least
> not in Python, there may be something in R, I have not looked).
>
> [1] https://www.jstor.org/stable/2957563
> [2] doi.org/10.1002/0471722162.ch7
> [3] https://perfeval.epfl.ch/
>
> @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> <https://docs.scipy.org/doc/scipy/reference/stats.html#statistical-tests>.
>
>
> That is also definitely interesting, although I am not myself an expert
> in that area. I am glad to see that the complete list contains some
> non-parametric tests :-)
>
> Cheers,
> --
> Romain
>
>
> On Mon, Jun 8, 2020 at 2:11 AM Romain Jacob <jacobr at ethz.ch> <jacobr at 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 Laboratorywww.romainjacob.net
> @RJacobPartner <https://twitter.com/RJacobPartner> <https://twitter.com/RJacobPartner>
> Gloriastrasse 35, ETZ G75
> 8092 Zurich
> +41 7 68 16 88 22
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> --
> Matt Haberland
> Assistant Professor
> BioResource and Agricultural Engineering
> 08A-3K, Cal Poly
>
> _______________________________________________
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>
> --
> Romain Jacob
> Postdoctoral Researcher
> ETH Zurich - Computer Engineering and Networks Laboratorywww.romainjacob.net
> @RJacobPartner <https://twitter.com/RJacobPartner> <https://twitter.com/RJacobPartner>
> Gloriastrasse 35, ETZ G75
> 8092 Zurich
> +41 7 68 16 88 22
> _______________________________________________
> SciPy-Dev mailing listSciPy-Dev at python.orghttps://mail.python.org/mailman/listinfo/scipy-dev
>
> --
> Matt Haberland
> Assistant Professor
> BioResource and Agricultural Engineering
> 08A-3K, Cal Poly
>
> _______________________________________________
> SciPy-Dev mailinglistSciPy-Dev at python.orghttps://mail.python.org/mailman/listinfo/scipy-dev
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> _______________________________________________
> SciPy-Dev mailing listSciPy-Dev at python.orghttps://mail.python.org/mailman/listinfo/scipy-dev
>
> --
> Matt Haberland
> Assistant Professor
> BioResource and Agricultural Engineering
> 08A-3K, Cal Poly
> _______________________________________________
> SciPy-Dev mailing listSciPy-Dev at python.orghttps://mail.python.org/mailman/listinfo/scipy-dev
>
> _______________________________________________
> SciPy-Dev mailing listSciPy-Dev at python.orghttps://mail.python.org/mailman/listinfo/scipy-dev
>
> --
> 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
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