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

From: Huntsinger, Reid <reid_huntsinger_at_merck.com>
Date: Fri 25 Mar 2005 - 02:23:35 EST

You'll really need to give some details if you want anything like a relevant answer. There aren't really general methods for dealing with discontinuous functions you can't compute.

A few things come to mind. 1) You might have a look at the literature on segmented regression. Non-differentiable and even discontinuous objective functions arise there. 2) Monte Carlo: you may be able to adapt one of the Monte Carlo optimization approaches to your situation, avoiding having to do Monte Carlo within Monte Carlo.

I'd be happy to be more specific if you'll supply details.

Reid Huntsinger

-----Original Message-----
From: r-help-bounces@stat.math.ethz.ch
[mailto:r-help-bounces@stat.math.ethz.ch] On Behalf Of Jean Eid Sent: Thursday, March 24, 2005 9:12 AM
To: Spencer Graves
Cc: r-help@stat.math.ethz.ch
Subject: Re: [R] non-derivative based optimization and standard errors.

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,
> >
> >______________________________________________
> >R-help@stat.math.ethz.ch mailing list
> >https://stat.ethz.ch/mailman/listinfo/r-help
http://www.R-project.org/posting-guide.html
> >
> >
>
>

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