[SciPy-Dev] GSoC'17: Circular statistics

[josef.pktd at gmail.com]

On Sat, Mar 11, 2017 at 2:50 PM, Vladislav Iakovlev <iavlaserg at gmail.com> wrote:
> Hello!
>
>
> My name is Vladislav Iakovlev. I am a master student of Department of
> Applied Math, HSE University, Moscow, Russia. I have never contributed to
> open source projects, but I would be happy to start it with SciPy.
>
>
> I noticed that existing functionality for circular statistics is
> insufficient. So, I want to suggest an idea for GSoC: implement it to
> scipy.stats. My plan is to do it through the next steps:
>
> 1)      Develop the class rv_circular, analogous to rv_continuous adjusted
> to circular statistic functions.
>
> 2)      Develop derived classes for circular distributions.
>
> 3)      Develop point estimations and statistical tests functions.
>
> During the summer, I assume to implement materials from chapters 1-8 of the
> book “MARDIA, K. V. AND JUPP , P. E. (2000), Directional Statistics, John
> Wiley”, documentation and unit tests for it.
>
>
> Is this idea interesting for the Community? I’m glad to any feedback.
>
>
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More general question: What should be the future of circular stats in python?

https://github.com/circstat/pycircstat is a python translation of the
matlab toolbox. It doesn't have a license (MIT is commented out in
setup.py) but the original matlab toolbox was BSD licensed on the file
exchange.

I worked on circularstats for several months in 2012 and didn't look
at it since then. I also translated the matlab toolbox and added some
more parts based on Mardia.
http://josef-pkt.github.io/pages/packages/circularstats/circular.html
table of content only, I never open sourced it. (*)
(Related: some work on mixtures of VonMises distributions
https://github.com/rc/dist_mixtures )
I looked into it briefly again
https://github.com/statsmodels/statsmodels/issues/3530 but mainly with
respect to adding regression with circular response variable.


(*) AFAIR, I didn't implement (m)any distribution in scipy
distribution style. I was looking mainly at generic constructors for
distributions, e.g. using wrapping to go from distribution on the real
line to distributions on the circle based on characteristic function
and fourier expansion.

Josef