[R] what is R best for? Evidence please.

[John C Nash]

Discussion about R capabilities seem to suggest that for optimization 
one may want to use some other software. As I've been working (with Ravi 
Varadhan mainly) to try to improve what is now called optim(), I needed 
to test some new methods, including a variant of CG. Coding only in R on 
a pretty vanilla 3Ghz PC, I was surprised that a generalized Rosenbrock 
function in n=50000 parameters solved in less than 2 minutes. It seems a 
lot of my experiences in building routines that appear in optim() -- 
which were written on a machine with 8K (that's K) bytes for program AND 
data -- are really not valid any more. This has prompted us to try (and 
it not simple) to set up some infrastructure to get good (well, better?) 
measures of performance for optimization and nonlinear parameter 
estimation. Complications involve the variety of environments and 
configurations, as well as codings of test functions, choices of how to 
provide gradient information etc. Contact me off-line if you are 
interested in this, as we would like it to be relatively easy to use and 
share. That can come only by communication, and we want to have lots of 
"real" tests, and they take a fair bit of effort to set up in a 
standardized way.

However, the main message here is to ask, as I was reasonably asked by 
another R worker, that people be much more cautious with conjectures. We 
can and should check our opinions by measuring, no matter what tasks or 
tools, when we give advice.

JN