I just put up my own statistics routines at
https://code.jsoftware.com/wiki/User:Devon_McCormick/myStats (also on
github).  It includes functions related to quartiles.  There's one called
"quartile" which returns the breakpoints for quartile x in vector y and
another called "ntilebps" which is a generalized n-tile routine so, for
example, x would be "4" for quartiles.


On Fri, Feb 26, 2021 at 8:08 AM chris burke <[email protected]> wrote:

> > I noticed for example that the sqlite package does this. The author
> forked the library, modified it so that its easier to integrate, and then
> bound J to it leaving code on both sides to maintain.
>
> Right, though we didn't modify the sqlite code itself, just extended
> it to allow J to read and write array arguments to sqlite. Without
> that extension, J would have to loop, e.g. record at a time, so this
> would slow things down. The only maintenance done is to recompile from
> a later sqlite source.
>
> On Fri, Feb 26, 2021 at 12:04 AM Emir U <[email protected]> wrote:
> >
> > Hey Devon, I think J's stat libraries are a basic start. the other day I
> wrote an interquartile range function because there wasn't one or a
> quantile function. Please compare the GNU Scientific list or an ok library
> like https://www.statsmodels.org/stable/api.html for gaps. PCA, PLS, KDE,
> MCMC, ME est., multivariate distributions, are bread and butter for my work
> but none of these things come with J. I personally think that binding a
> different language (e.g. R) and then calling stats functions from it is at
> best a stop gap but not a solution in itself. That's for example something
> that Julia does whilst they hustle to cover all basis. I.e. worst case
> scenario, call Python from Julia. What happens in practice is that you just
> end up writing stuff in both languages in order to facilitate the
> integration which I don't like for maintenance. I noticed for example that
> the sqlite package does this. The author forked the library, modified it so
> that its easier to integrate, and then bound J to it leaving code on both
> sides to maintain.
> >
> > Hey Bill, I've also used Stan a lot in the last 1.5 years. I've used
> both the R and Python packages extensively, and tbh I find the integrations
> pretty clunky. I think part of the reason is that Stan has a DSL so you end
> up either writing the code in a file and referencing that or having big
> multi-line strings in which your model is embedded. I personally prefer
> PyMC3 or Nimble type integrations. Just a thought but I think a better way
> to grow would be to integrate the SGLD and NUTS routines from Tensorflow
> probability, and then specify likelihoods directly in J if that's possible.
> However, it means having much better support for commonplace uni/multi
> variate distributions at the least.
> >
> > Emir
> > ----------------------------------------------------------------------
> > For information about J forums see http://www.jsoftware.com/forums.htm
> ----------------------------------------------------------------------
> For information about J forums see http://www.jsoftware.com/forums.htm
>


-- 

Devon McCormick, CFA

Quantitative Consultant
----------------------------------------------------------------------
For information about J forums see http://www.jsoftware.com/forums.htm

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