Re: [R] difference between nlm and nlminb

From: DavidM.UK <david.merritt_at_bris.ac.uk>
Date: Thu, 12 Jun 2008 02:53:25 -0700 (PDT)

Thank you for those details, the only optimization routine I've come accross outside of CRAN is:
http://www.stat.umn.edu/geyer/trust/

Personally I only use nlminb for the estimation of Time Series models, which typically have well defined limits for the elements of the parameter vector - so in my post I guess as a "high level" explaination I was stressing in reality you'd use nlm for unconstrained and nlminb for constrained (and as you point out box constraints) optimization as the "take home" point.

I notice the R group where taking part in the "Google summer of code 2008" event - perhaps a useful project could be the implementation of numerous optimization routines in R?

Thanks

David

Douglas Bates-2 wrote:
>
> nlminb provides unconstrained optimization and optimization subject to
> box constraints (i.e. upper and/or lower constraints on individual
> elements of the parameter vector). The nlm function provides
> unconstrained optimization.
>
> I created the nlminb function because I was unable to get reliable
> convergence on some difficult optimization problems for the nlme and
> lme4 packages using nlm and optim. The nlme package was originally
> written for S from Bell Labs (the forerunner of S-PLUS) and the PORT
> package was the optimization code used. Even though it is very old
> style Fortran code I find it quite reliable as an optimizer. It
> allows for what is called reverse communication which is convenient in
> an environment like R. It is a technical issue that has to do with
> what code is in control when your R expression needs to be evaluated.
>
> That said, I still don't feel that I have seen good, modern
> Open-Source optimization code. I would welcome suggestions of where
> one might find such code.
>
>
> On Wed, Jun 11, 2008 at 3:16 AM, DavidM.UK <david.merritt_at_bris.ac.uk>
> wrote:

>>
>> I believe nlminb() performs *constrained* optimization, where as nlm() is
>> for
>> *unconstrained* opimization
>>
>> So I guess nlm() is for solving min(f[a,b]), and nlminb() min(f[a,b])
>> given
>> a+b <= c
>>
>> FYI I think optim() also does constrained optimization, well I've used
>> for
>> min(f[a,b]) given a <= a* and b <= b*.
>>
>> David
>>
>>
>> ae2356 wrote:
>>>
>>>
>>> Hi,
>>>
>>> I was wondering if someone could give a brief, big picture overview of
>>> the
>>> difference between the two optimization functions nlm and nlminb. I'm
>>> not
>>> familiar with PORT routines, so I was hoping someone could give an
>>> explanation.
>>>
>>> Thanks,
>>> Angelo
>>> _________________________________________________________________
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>>
>> --
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>>
>> ______________________________________________
>> R-help_at_r-project.org mailing list
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>
> ______________________________________________
> R-help@r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>
>


David Merritt
Postgrad [Statistics]
University of Bristol, UK
-- 
View this message in context: http://www.nabble.com/difference-between-nlm-and-nlminb-tp17769859p17796362.html
Sent from the R help mailing list archive at Nabble.com.

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