Dear Johann and Gabor, It's what amounts to large datasets. There are hundreds of datasets R can't handle, probably thousands or more. I noticed on my computer (which is nothing more that an average PC) that R breaks down after 250 MB of memory. I also note that SPSS breaks down, Matlab, etc.
I'm not a SAS user, but I have worked in the past with SAS. It's very good as a remember, but it's ten years ago. And it's a "dollar machine" I've been told: you add dollars to SAS as you add dollars to a Porsche. I haven't got it and for most statistical applications it isn't necessary I've been told. R is sufficient for that. The datasets I use are often not that big (the way I like it). About three years ago I spoke to somebody who has worked with it and said "it's database system is excellent and statistical profound". Someone with a PhD, so probably he is right. Monte-Carlo simulations are computationally time-consuming, but probably these can be done in R. I haven't seen any libaries for it (they might be there). It has been done with S (the commercial counterpart of R), so probably with R too. If you tie Monte Carlo simulaton with large datasets you probably run into problems with a conventional R system. What I've been told in those instances is "buy a new computer" / "add memory and buy a new processor"... and don't smoke hashiesh. That wasn't a good advice because the guy who told me smoked hashiesh like hell and drank Pastis (blue liqor) like water. I kicked him out. But that's another story. Cheers, Wilfred (I drink wine and tailor made beer, and only on occasions. That's why. His simulations were good I've been told.) ______________________________________________ [email protected] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
