[SciPy-Dev] k-sample Anderson Darling test

[josef.pktd at gmail.com]

On Fri, Jan 3, 2014 at 2:29 PM, Joerg Dietrich <joerg at joergdietrich.com> wrote:
> On Thu, Jan 02, 2014 at 08:22:55AM -0500, josef.pktd at gmail.com wrote:
>> On Thu, Jan 2, 2014 at 7:48 AM, Joerg Dietrich <joerg at joergdietrich.com> wrot> > I have code that implements the k-sample Anderson Darling test (Scholz
>>
>> This would be a good contribution to scipy.stats (or to statsmodels).
>
> There's code
> https://github.com/joergdietrich/scipy/compare/k-sample-AD ready for a
> review. Or should I send a PR right away?

You could send the PR right away, it will make it easier to add line
comments and discuss.

Overall looks good.

The main thing we should check is whether and how to get rid of some
of the loops.
It has been a while since I looked at this, but as far as I remember
there should be some numpy shortcuts to avoid at least some of the
loops.

The main thing that puzzles me from a quick look is the use of
np.unique and `==` (line 1232) when we assume continuous variables,
where all values "should" be unique.

Josef


>
> Cheers,
>         Joerg
>
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