J, R, and statistical programming

I'm not sure why statisticians are so enamored of single-letter names for their programming systems (makes Googling very difficult), but there you go.  I knew of R, of course, from the existence of CRAN alone, but today I found out about J.

One of J's original authors is Ken Iverson of APL fame.  And yeah, in terms of its compositionality and frank strangeness for imperative programmers like myself, it looks a lot like ... well, like a usable APL, really.  So how does it stack up against R?  Ask StackOverflow: the short answer is ... it's complicated.  R has fantastic third-party library support, but J can run R.  R is more verbose and therefore probably easier to maintain.  On the other hand, for data manipulation, J is succinct and expressive.  So it really depends on what you're doing, which is increasingly the case for programming languages these days.

J has a full-featured runtime environment and IDE, too.  This alone would make it interesting: J is built from the ground up to build things.  Things that will be used by people.  You can package a J app and use J's own installer to distribute your software.  There are GUI and graphics tools built into the language and its basic library system.

In this sense, it would be a great model for some hypothetical standalone Decl system.