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using optimize() correctly ...

Yes.  Most classical optimization methods (e.g. gradient-type, Newton-type) are "local", i.e. they do not attempt to locate the global optimum.  The primary difficulty with global optimization is that there are no mathematical conditions that characterize global optimum in multi-modal problems.  For local optimum, you have the first- and second-order Kuhn-Tucker conditions.  A simplistic strategy to find global optimum is to use local methods with multiple starting values.  Again the problem is that you don't haev any guarantee that you have found the global optimum.  The larger the number of starting values, the greater your chances of finding the global optimum.  There are more principled strategies than the random multi-start approach, but even they are not guaranteed to work.  

Ravi.

____________________________________________________________________

Ravi Varadhan, Ph.D.
Assistant Professor,
Division of Geriatric Medicine and Gerontology
School of Medicine
Johns Hopkins University

Ph. (410) 502-2619
email: rvaradhan at jhmi.edu


----- Original Message -----
From: Esmail <esmail.js at gmail.com>
Date: Sunday, May 24, 2009 8:27 am
Subject: Re: [R] using optimize() correctly ...
To: Berend Hasselman <bhh at xs4all.nl>
Cc: r-help at r-project.org