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.
Doug, Agreed on the interesting point - looks like it has some real promise. I think the spike in interest could be attributable to Mike Loukides's tweet on Feb 20. (editor at O'Reilly) https://twitter.com/#!/mikeloukides/status/171773229407551488 That is exactly the moment I stumbled upon it. Jeff On Thu, Mar 1, 2012 at 11:06 AM, Douglas Bates <bates at stat.wisc.edu> wrote:> 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 at r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-devel-- Jeffrey Ryan jeffrey.ryan at lemnica.com www.lemnica.com www.esotericR.com R/Finance 2012: Applied Finance with R www.RinFinance.com See you in Chicago!!!!
On Thu, Mar 01, 2012 at 11:06:51AM -0600, Douglas Bates wrote:> 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.[...] Very interesting language. Thank you for mentioning it here. Compiling from the github-sources was easy. Will explore it during the next days. Seems not to be very specific to statistics, but good for math in general. Not sure, if it might make sense to combine R and Julia in the long run (I mean: combining via providing interfaces between them, calling the one via the other, merging code or using libs from the one or the other from each side). Ciao, Oliver
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