# [R-sig-ME] Suggestions for numerical optimization tools...

Doran, Harold HDoran at air.org
Wed Apr 22 18:20:04 CEST 2009

If the likelihood can be written out, why would the derivatives not be
known?

> -----Original Message-----
> From: r-sig-mixed-models-bounces at r-project.org
> [mailto:r-sig-mixed-models-bounces at r-project.org] On Behalf Of H c
> Sent: Wednesday, April 22, 2009 12:04 PM
> To: r-sig-mixed-models at r-project.org
> Subject: [R-sig-ME] Suggestions for numerical optimization tools...
>
> My current program relies on the ML estimation of a
> parameter, \phi,  based on numerical methods.  The parameter,
> \phi,  lies on the 0 to 1 interval and evaluation of the ML
> given any value of \phi is computationally expensive.
>  I am currently using the "optimize()" function, optimizing
> the Likelihood with respect to phi.  This is extremely
> computationally expensive and is the bottleneck of an
> otherwise efficient program.
> Does anyone have any suggestions of better tools for
> numerical optimization.
>  (Derivatives are not known, so gradient decent options do
> not appear to be applicable).
>
> Anything helps,
>
> Harlan
>
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