My purpose in mentioning the Julia language (julialang.org) here is not to start a flame war. I find it to be a very interesting development and others who read this list may want to read about it too.
It is still very much early days for this language - about the same stage as R was in 1995 or 1996 when only a few people knew about it - but Julia holds much potential. There is a thread about "R and statistical programming" on groups.google.com/group/julia-dev. As always happens, there is a certain amount of grumbling of the "R IS SOOOO SLOOOOW" flavor but there is also some good discussion regarding features of R (well, S actually) that are central to the language. (Disclaimer: I am one of the participants discussing the importance of data frames and formulas in R.) If you want to know why Julia has attracted a lot of interest very recently (like in the last 10 days), as a language it uses multiple dispatch (like S4 methods) with methods being compiled on the fly using the LLVM (http://llvm.org) infrastructure. In some ways it achieves the Holy Grail of languages like R, Matlab, NumPy, ... in that it combines the speed of compiled languages with the flexibility of the high-level interpreted language. One of the developers, Jeff Bezanson, gave a seminar about the design of the language at Stanford yesterday, and the video is archived at http://www.stanford.edu/class/ee380/. You don't see John Chambers on camera but I am reasonably certain that a couple of the questions and comments came from him. ______________________________________________ R-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-devel