On Wed, Sep 8, 2010 at 1:35 PM, Michael Bernsteiner
<dethl...@hotmail.com> wrote:
>
> Dear all,
>
> I'm optimizing a relatively simple function. Using optimize the optimized
> parameter value is worse than the starting.
> why?
>
> f<-function(delta,P,U){
> minimiz<-P+delta*U
> x<-minimiz[1]
> y<-minimiz[2]
> z<-100*(y-x^2)^2+(1-x)^2
> return(z)
> }
This looks familiar. Is this some 1-d version of the Rosenbrock
Banana Function?
http://en.wikipedia.org/wiki/Rosenbrock_function
It's designed to be hard to find the minimum. In the real world one
would hope that things would not have such a pathological behaviour.
Numerical optimisations are best done using as many methods as
possible - see optimise, nlm, optim, nlminb and the whole shelf of
library books devoted to it.
Barry
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