Tony Long <tdlong at uci.edu> wrote:
I agree that R is not "designed" for large calculations. On the other hand it is nice to have one statistical package to use for all calculations. I mostly deal with Drosophila and DNA, as such I am an amateur statistician and would like to avoid learning a number of statistical languages. With a big Linux box, I can often power through things. In the past I have found it frustrating to do a bunch of stuff in SAS only to hit a snag and then have to write (time consuming) "C" code to finish the job. So although not designed for large calculations, R is so flexible and logical that it is very attractive to use it for such...I think that many other people may be similarly attracted to the language. I would appreciate dialog, as I think that much more may have been accomplished in R than was intended by the founders.
R's poor handling of large datasets is half the reason I have not moved more of my work from S(plus) to R (the other half being the absence of trellis). I love its lexical closures, but they're not worth the memory penalty if you have huge datasets. Maybe someday R will get something akin to Perl's 'tie' mechanism that would allow practical analysis of huge datasets. Maybe that's not possible. --Todd
Z. Todd Taylor Pacific Northwest National Laboratory Todd.Taylor at pnl.gov Why does cleave mean both separate and adhere? -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the subject !) To: r-help-request at stat.math.ethz.ch _._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._