Incanter is quite nice and I really like Clojure (disclaimer: I am still a beginner), but it has far less libraries than R. I also think the creators of R did a really good job in making seamless the installation of a package (install.packages(...)) and having lots of functions pretty well documented, so a statistician who is not a programmer can easily do his work and quickly come up with results. AFAIK this is still unmatched anywhere else.

Perhaps as importantly, R has significant buy-in in the statistics community, so a paper on a new technique will often be accompanied by an R package implementing it; in fact several journals explicitly prefer R packages for accompanying code, because the reviewers are likely to be familiar with how to use it. That's partly due to its semi-continuity with Bell Labs S (http://en.wikipedia.org/wiki/S_(programming_language)), I believe, which was a language designed by-statisticians-for-statisticians. It's fairly hard to replicate that; would require considerable effort to migrate the whole community to a new consensus environment.