I came across a quite interesting post from Ross Ihaka, thought would be good to share it and get the opinion of folks around here. I am not sure where to post this for the R community but since it has to do with development I thought or R-devel
Ross Ihaka Newsgroups: comp.lang.lisp From: Ross Ihaka <[EMAIL PROTECTED]> Date: Wed, 23 Jan 2008 10:35:26 +1300 Local: Tues, Jan 22 2008 11:35 pm Subject: Re: Is Xlisp-Stat Dead? Rainer Joswig wrote: > In article > <[EMAIL PROTECTED]>, > Robert <[EMAIL PROTECTED]> wrote: >> Did the founders of R cut it's head off? >> Did SAS and SPSS chop it to pieces? >> What happened to it? > See: http://repositories.cdlib.org/uclastat/papers/2004062201/ > On Abandoning Xlisp-Stat > Jan de Leeuw, UCLA Department of Statistics I'm one of the two originators of R. After reading Jan's paper I wrote to him and said I thought it was interesting that he was choosing to jump from Lisp to R at the same time I was jumping from R to Common Lisp. Building something like R is a big task though. The capabilities in R reflect the specialist contributions of hundreds of research statisticians. Currently there is a very small group of us scoping out ways to create a Lisp-based framework in which similar contributions could be made. ... A a little further: Newsgroups: comp.lang.lisp From: Ross Ihaka <[EMAIL PROTECTED]> Date: Wed, 23 Jan 2008 12:42:14 +1300 Local: Wed, Jan 23 2008 1:42 am Subject: Re: Is Xlisp-Stat Dead? Reply to author | Forward | Print | Individual message | Show original | Report this message | Find messages by this author Ken Tilton wrote: > So how come an originator of something with the momentum and mindshare > of R is swimming against the current, and one he helped set in motion to > boot? We started work on R in the early '90s. At the time decent Lisp implementations required much more resources than our target machines had. We therefore wrote a small scheme-like interpreter and implemented over that. Being rank amateurs we didn't do a great job of the implementation and the semantics of the S language which we borrowed also don't lead to efficiency (there is a lot of copying of big objects). R is now being applied to much bigger problems than we ever anticipated and efficiency is a real issue. What we're looking at now is implementing a thin syntax over Common Lisp. The reason for this is that while Lisp is great for programming it is not good for carrying out interactive data analysis. That requires a mindset better expressed by standard math notation. We do plan to make the syntax thin enough that it is possible to still work at the Lisp level. (I believe that the use of Lisp syntax was partially responsible for why XLispStat failed to gain a large user community). The payoff (we hope) will be much greater flexibility and a big boost in performance (we are working with SBCL so we gain from compilation). For some simple calculations we are seeing orders of magnitude increases in performance over R, and quite big gains over Python. There is lots to do. We're experimenting with syntax and making a start on assembling quality numerics libraries. Creating a fully-featured system will require buy-in from the statistical specialists who can contribute implementations of their methodology, so we also thinking about issues associated with community building (eg. licensing). -- View this message in context: http://www.nabble.com/Ross-Ihaka%27s-reflections-on-Common-Lisp-and-R-tp17100237p17100237.html Sent from the R devel mailing list archive at Nabble.com. ______________________________________________ R-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-devel
