[Rd] Optimization in R

[Nicholas Lewin-Koh]

Hi,
In my earlier post I eluded to a situation where that would be useful. 
In nlme, there is a choice of optimizers, minpack.lm has
Levenberg-Marquardt,
while nlminb has the port routines. For the same starting values,
different
optimizers will present different solutions, having a common interface
would make fitting with multiple optimizers very attractive. 

Also the inverse Hessian would be useful, for cases where the Hessian is
ill conditioned
a little regularization goes a long way. I believe the package accuracy 
has a nice solution.

Nicholas
 

On 04/08/2007 2:23 PM, Gabor Grothendieck wrote:
> For the same reason that generic functions exist.  They don't have
> a lot of common code but it makes easier to use.  Perhaps the argument
> is not as strong here since the class tends to be implicit whereas the
> method is explicit but it would still be a convenience.

Can you give other examples where we do this?  The ones I can think of 
(graphics drivers and finalizers) involve a large amount of common 
machinery that it's difficult or impossible for the user to duplicate. 
That's not the case here.

Duncan Murdoch