Since Python is not held to backwards compatibility with S, and for most
datasets (and users) it doesn't matter much, why not ho with the default
recommended by Hyndman & Fan?

On Fri, Mar 16, 2018 at 11:48 PM, Nathaniel Smith <n...@pobox.com> wrote:

> On Fri, Mar 16, 2018 at 11:19 PM, Stephen J. Turnbull
> <turnbull.stephen...@u.tsukuba.ac.jp> wrote:
> > PLIQUE Guillaume writes:
> >
> >  > That's really interesting. I did not know there were so many way to
> >  > consider quantiles. Maybe we should indeed wait for numpy to take a
> >  > decision on the matter and go with their default choice so we remain
> >  > consistent with the ecosystem?
> >
> > The example of R with 9 variants baked into one function suggests that
> > numpy is unlikely to come up with a single "good" choice.  If R's
> > default is to Steven's taste, I would say go with that for cross-
> > language consistency, and hope that numpy makes the same decision.  In
> > fact, I would argue that numpy might very well make a decision for a
> > default that has nice mathematical properties, while the stdlib module
> > might very well prefer consistency with R's default since defaults
> > will be used in the same kind of "good enough for government work"
> > contexts in both languages.
>
> NumPy already has a default and supports a number of variants. I'd
> have to go digging to figure out which languages/tools use which
> methods and how those match to theoretical properties, but IIRC numpy,
> R, and matlab all have different defaults.
>
> The 9 types that R supports come from a well-known review article
> (Hyndman & Fan, 1996). Their docs note that Hyndman & Fan's
> recommendation is different from the default, because the default was
> chosen to match a previous package (S) before they read Hyndman & Fan.
> It's all a bit messy.
>
> None of this is to say that Python shouldn't have some way to compute
> quantiles, but unfortunately you're not going to find TOOWTDI.
>
> -n
>
> --
> Nathaniel J. Smith -- https://vorpus.org
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