[R] Comparison of SAS & R/Splus
Brian D Ripley
ripley at stats.ox.ac.uk
Fri Sep 5 11:02:45 CEST 2003
> On Thu, 4 Sep 2003, Paul, David A 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.
> While I don't subscribe to the general theory, they have a point about
> PROC NLMIXED. It does more accurate calculations for generalised linear
> mixed models than are currently available in R/S-PLUS, and for
> logistic random effects models the difference can sometimes be large
> enought to matter.
Yes. Except that I have access to several other codes for GLMM, and
not infrequently the answers from NLMIXED are out of line with
all of the others, and are sometimes just not credible. So
'more accurate' is as far as I am concerned remains to be proved
In general I find such discussions irrelvant. I bet those users
make far, far more errors then any of these packages do so.
Brian D. Ripley, ripley at stats.ox.ac.uk
Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
University of Oxford, Tel: +44 1865 272861 (self)
1 South Parks Road, +44 1865 272866 (PA)
Oxford OX1 3TG, UK Fax: +44 1865 272595
More information about the R-help