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

Sat Jun 13 14:54:47 EDT 2020

On Fri, Jun 12, 2020 at 11:29 AM <josef.pktd at gmail.com> wrote:

>
>
> 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)
>

I found my version again
https://github.com/statsmodels/statsmodels/issues/6562#issuecomment-592769480

I guess that's the same for two sided confint as the references.
It doesn't have interpolation if that could be applied in this case.

This will eventually end up in statsmodels, but I don't know yet where.
That's not a reason not to add it to scipy.stats.

Josef

>
> 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
>> _______________________________________________
>> 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
>>
>> --
>> 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
>>
>> _______________________________________________
>> 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
>> _______________________________________________
>> SciPy-Dev mailing list
>> SciPy-Dev at python.org
>> https://mail.python.org/mailman/listinfo/scipy-dev
>>
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