> 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
