Thanks Mike, I'm a J neophyte so take this with a pinch of salt. I think that
the best way to make J relevant for statistics is well thought through deep
bindings to the following libraries: GNU Plot, GNU Scientific. Not clunky write
to a file then run it in the background type stuff, but well thought through
data types and the ability to seamlessly pipe one thing into the next. That's
well over 1000 functions all together including practically everything. It'd be
sheer bliss for the esoteric mathematical statistician in my opinion and
something truly different to the usual throw-up between R/Python/Julia. Emir
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