On Thu, 04 Sep 2003 14:50:25 -0400 "Paul, David A" <[EMAIL PROTECTED]> wrote:
> I am one of only 5 or 6 people in my organization making the > effort to include R/Splus as an analysis tool in everyday work - > the rest of my colleagues use SAS exclusively. > > Today, one of them made the assertion that he believes the > numerical algorithms in SAS are superior to those in Splus > and R -- ie, optimization routines are faster in SAS, the SAS > Institute has teams of excellent numerical analysts that > ensure its superiority to anything freely available, PROC > NLMIXED is more flexible than nlme( ) in the sense that it > allows a much wider array of error structures than can be used > in R/Splus, &etc. > > I obviously do not subscribe to these views and would like > to refute them, but I am not a numerical analyst and am still > a novice at R/Splus. Do there exist refereed papers comparing the > numerical capabilities of these platforms? If not, are there > other resources I might look up and pass along to my colleagues? > > > > Much thanks in advance, > > david paul I don't have papers comparing the numerical capabilities but I say bunk to your colleagues. The last time I looked, SAS still relies on the out of date Gauss-Jordan sweep operator in many key places, in place of the QR decomposition that R and S-Plus use in regression. And SAS being closed source makes it impossible to see how it really does calculations in some cases. See http://hesweb1.med.virginia.edu/biostat/s/doc/splus.pdf Section 1.6 for a comparison of S and SAS (though this doesn't address numerical reliability). Overall, SAS is about 11 years behind R and S-Plus in statistical capabilities (last year it was about 10 years behind) in my estimation. Frank Harrell SAS User, 1969-1991 --- Frank E Harrell Jr Professor and Chair School of Medicine Department of Biostatistics Vanderbilt University ______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
