An old rule of thumb was that you should have 6 times as much memory as your dataset will take. But I think pretty much everything has been improved since then, so you should be able to get by with less (others may be able to give a better rule of thumb these days).
You might want to look at the biglm package, it allows you to do regression models with only a portion of your data loaded at a time, allowing for pretty much any size of data set in a limited memory situation. Hope this helps, -- Gregory (Greg) L. Snow Ph.D. Statistical Data Center Intermountain Healthcare [EMAIL PROTECTED] (801) 408-8111 > -----Original Message----- > From: [EMAIL PROTECTED] > [mailto:[EMAIL PROTECTED] On Behalf Of ivo welch > Sent: Saturday, February 10, 2007 11:03 AM > To: r-help@stat.math.ethz.ch > Subject: [R] practical memory limits > > Dear R experts: I want to learn what the practically useful > memory limits are for good work with R. > > (My specific problem is that I want work with daily stock returns. > In ASCII, the data set is about 72 million returns, that > would have to go into a sparse matrix (not all stocks exist > for the whole series). > As a guess, this will consume about 700MB. My main use will > be linear operations---regressions, means, etc.) > > I am on linux, so I can create swap space, but I am concerned > that the thrashing will be so bad that the computer will > become worthless. In fact, the last time I used it was over > 3 years ago. Since then, I have just turned it off. > > I have 2GB of RAM right now, and could upgrade this to 4GB. > > Are there some general guidelines as to what the relationship > between data sets and memory should be under R? I know this > will vary with the task involved, but some guidance would be > better than none. > > regards, > > /iaw > > ______________________________________________ > R-help@stat.math.ethz.ch 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. > ______________________________________________ R-help@stat.math.ethz.ch 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.