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

[Hans Dembinski]

Dear all,

since there was no reply to my first attempt, I am repeat my message. Daniel Saxton and I are working on a Python library called `resample`, which implements the bootstrap and jackknife. We would like to work toward merging bootstrap functions into Scipy and it would be great to get some feedback about this. We would be pleased to collaborate with people who are already working on this in Scipy. We are both pretty decent programmers, knowledgable about statistics in general and the bootstrap in particular.

Best regards,
Hans

> On 12. Jun 2020, at 16:16, Hans Dembinski <hans.dembinski at gmail.com> wrote:
> 
> I just joined the list, so I apologise for any etiquette-breaking in advance, but would like  to inject here that I am collaborating with Daniel Saxton on `resample`, a library that implements the jackknife and bootstrap, which can be used - among many other things - to compute confidence intervals for quantiles/percentiles.
> 
> https://github.com/dsaxton/resample
> 
> We are currently working on interface and documentation and adding more unit tests and benchmarks, but `resample` is already the most complete library that implements resampling methods in Python. 
> 
> Seeing that https://github.com/scipy/scipy/issues/10577 explicitly mentions bootstrapping, we are interested in merging our work into scipy. We use the BSD 3-clause license, so the license should not be an issue. Is there already work ongoing on bootstrap methods? With whom should we collaborate?
> 
> Some context about us:
> 
> Daniel is a data analyst working in the financial industry. I am a particle physicist and the author of Boost Histogram (C++ and Python, https://github.com/boostorg/histogram, https://github.com/scikit-hep/boost-histogram) and the maintainer of iminuit, the general purpose minimiser and error computer (C++ and Python, https://github.com/scikit-hep/iminuit).
> 
> Best regards,
> Hans
>