[R] Comparison of SAS & R/Splus
MSchwartz at medanalytics.com
Thu Sep 4 22:12:55 CEST 2003
On Thu, 2003-09-04 at 08:34, Frank E Harrell Jr wrote:
> On Thu, 04 Sep 2003 14:50:25 -0400
> "Paul, David A" <paulda at BATTELLE.ORG> 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 the out of date Gauss-Jordan sweep operator in many key places, in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
In follow up to Frank's reply, allow me to point you to some additional
papers and articles on numerical accuracy issues. I have not reviewed
these in some time and they may be a bit dated relative to current
versions. These do not cover R specifically, but do address S-Plus and
SAS. This is not an exhaustive list by any means, but many of the papers
do have other references that may be of value.
Another option is that NIST has reference datasets available for comparison at:
These would allow you to conduct your own comparisons if you desire.
(Also a former SAS user)
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