This stuff is of course dependent on exactly which optimization problem you
have, but optimx::optimr is often a very good drop-in replacement for optim,
especially when bounds are involved (e.g., optim has an awkward habit of
attempting evaluations outside the domain when numerical derivatives are
needed).
You might want to look at the last examples in ?stats4::mle (in R 4.x.x)
-pd
> On 10 Aug 2020, at 22:08 , Roy Mendelssohn - NOAA Federal via R-help
> <r-help@r-project.org> wrote:
>
> I am running a lot of optimization problems, at the moment using 'optim'
> ('optim' is actually called by another program). All of the problems have
> variables with simple upper and lower bounds, which I can easily transform
> into a form that is unconstrained and solve using 'BFGS'. But I was
> wondering is if it is more robust to solve the problem this way, or to use
> L-BFGS-B instead.
>
> Also how much difference can it make using 'optimx' instead 'optim'? The
> program I am using (KFAS) allows this, I just have to do some extra
> programming to use it.
>
> Thanks,
>
> -Roy
>
>
>
> **********************
> "The contents of this message do not reflect any position of the U.S.
> Government or NOAA."
> **********************
> Roy Mendelssohn
> Supervisory Operations Research Analyst
> NOAA/NMFS
> Environmental Research Division
> Southwest Fisheries Science Center
> ***Note new street address***
> 110 McAllister Way
> Santa Cruz, CA 95060
> Phone: (831)-420-3666
> Fax: (831) 420-3980
> e-mail: roy.mendelss...@noaa.gov www: https://www.pfeg.noaa.gov/
>
> "Old age and treachery will overcome youth and skill."
> "From those who have been given much, much will be expected"
> "the arc of the moral universe is long, but it bends toward justice" -MLK Jr.
>
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--
Peter Dalgaard, Professor,
Center for Statistics, Copenhagen Business School
Solbjerg Plads 3, 2000 Frederiksberg, Denmark
Phone: (+45)38153501
Office: A 4.23
Email: pd....@cbs.dk Priv: pda...@gmail.com
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