One approach econometricians use with linear models is to demean the data in order to reduce the computational burden. This can be done using the ave() function. But, this is still difficult because, in my experience, you still need to build a model matrix that must be demeaned and that model matrix may be big. On the other hand, if you're dealing with large sparse data sets, you may find either the sparseM and Matrix packages useful as they are designed to handle large sparse matrices.
> -----Original Message----- > From: [EMAIL PROTECTED] > [mailto:[EMAIL PROTECTED] On Behalf Of Dietrich Trenkler > Sent: Wednesday, November 07, 2007 3:05 AM > To: R-help > Subject: [R] Using R for large econometric models > > Dear helpeRs, > > a colleague of mine would like to give R a try. He uses > econometric models which typically involve a large number of > variables, esp. time series. Having no experience with > handling very large data sets myself I turn to you. > > 1. Could you please describe your experiences to cope with these > situations? > > 2. What kind of difficulties will he have to face? Are there special > tricks (packages) he might try? > > 3. Can you recommend to use R? > > > Sorry, if my question is a bit vague but at this point I'm > not able to give any further details. > > Any help is very much appreciated. > > D. Trenkler > > -- > Dietrich Trenkler c/o Universitaet Osnabrueck > Rolandstr. 8; D-49069 Osnabrueck, Germany > email: [EMAIL PROTECTED] > > ______________________________________________ > R-help@r-project.org 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@r-project.org 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.
