[R] non-derivative based optimization and standard errors.

[Ingmar Visser]

Hi Jean,

Profiling may be another option and/or finite difference gradients.

In any case, if your objective function is discontinuous at some point close
to the optimal parameter values, standard errors may not make much sense.

Best, Ingmar


On 3/24/05 9:12 AM, "Jean Eid" <jeaneid at chass.utoronto.ca> wrote:

> The problem is that it is a very complicated model and bootstrap will
> probably take months. The objective function itself is making use of Monte
> Carlo simulation because it is next to impossible to get at a closed form
> solution (of the objective function itself). So I simulate this function
> and get its expectation and match that to data. I thought of doing a
> bootstrap but it will take so much time. I guess if this is the only way,
> then it has to be done.
> 
> 
> Jean
> 
> On Wed, 23 Mar 2005, Spencer Graves wrote:
> 
>>       Have you considered bootstrap or Monte Carlo?
>> 
>>       spencer graves
>> 
>> Jean Eid wrote:
>> 
>>> Hi AlL,
>>> 
>>> I ahve this problem that my objective function is discontinous in the
>>> paramaters and I need to use methods such as nelder-mead to get around
>>> this. My question is: How do i compute standard errors to a problem that
>>> does not have  a gradient?
>>> 
>>> 
>>> Any literature on this is greatly appreciated.
>>> 
>>> 
>>> Jean,
>>> 
>>> ______________________________________________
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>>> 
>>> 
>> 
>> 
> 
> ______________________________________________
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-- 
Ingmar Visser
Department of Psychology, University of Amsterdam
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