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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