R help - Jul 2010 - Not nice behaviour of nlminb (windows 32 bit, version, 2.11.1)

I won't add to the quite long discussion about the vagaries of nlminb, but
will note that
over a long period of software work in this optimization area I've found a
number of
programs and packages that do strange things when the objective is a function of
a single
parameter. Some methods quite explicitly throw an error when n<2. It seems
nlminb does
not, but that does not mean that the authors ever thought anyone would use their
large
package to solve a small 1D problem, or if they did, whether they seriously
tested for the
awkward things that happen when one only has one parameter. I've seen
similar things go
wrong with matrix packages e.g., eigensolutions of 1 by 1 matrices.

So this msg is to watch carefully when problems are n=1 and put in some checks
that
answers make sense.

JN

On 10/07/2010 9:48 AM, Prof. John C Nash wrote:
> I won't add to the quite long discussion about the vagaries of nlminb,
but will note that
> over a long period of software work in this optimization area I've
found a number of
> programs and packages that do strange things when the objective is a
function of a single
> parameter. Some methods quite explicitly throw an error when n<2. It
seems nlminb does
> not, but that does not mean that the authors ever thought anyone would use
their large
> package to solve a small 1D problem, or if they did, whether they seriously
tested for the
> awkward things that happen when one only has one parameter. I've seen
similar things go
> wrong with matrix packages e.g., eigensolutions of 1 by 1 matrices.
>
> So this msg is to watch carefully when problems are n=1 and put in some
checks that
> answers make sense.

This has nothing to do with n=1. 

nlminb(obj = function(x) sum(x^2)-25, start = c(0,6))

fails as badly as all the other examples.  The problem is the 
(unintended?) assumption in nlminb, and possibly in the PORT library it 
uses, that f(x) is non-negative, so a vector x where f(x) = 0 is 
guaranteed to be a solution.

Duncan Murdoch