R help - Jul 2011 - Very slow optim()

Dear list, 

 

I am using optim() function to MLE ~55 parameters, but it is very slow to
converge (~ 25 min), whereas I can do the same in ~1 sec. using ADMB, and ~10
sec using MS EXCEL Solver.

Are there any tricks to speed up?

Are there better optimization functions? 

 

Thanks

 

Toshihide "Hamachan" Hamazaki, $B_@:j=S=((JPhD

Alaska Department of Fish and Game: $B%"%i%9%+=#5y6HLn@8F0J*2](J

Diivision of Commercial Fisheries: $B>&6H5y6HIt(J

333 Raspberry Rd.  Anchorage, AK 99518

Phone:  (907)267-2158

Cell:  (907)440-9934

 


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Hamazaki, Hamachan (DFG <toshihide.hamazaki <at> alaska.gov> writes:
> 
> Dear list, 
> 
> I am using optim() function to MLE ~55 parameters, but it is very slow to
converge (~ 25 min), whereas I can do
> the same in ~1 sec. using ADMB, and ~10 sec using MS EXCEL Solver.
> 
> Are there any tricks to speed up?
> 
> Are there better optimization functions? 
> 
  There's absolutely no way to tell without knowing more about your code. 
You
might try method="CG":

    Method ?"CG"? is a conjugate gradients method based on that by
     Fletcher and Reeves (1964) (but with the option of Polak-Ribiere
     or Beale-Sorenson updates).  Conjugate gradient methods will
     generally be more fragile than the BFGS method, but as they do not
     store a matrix they may be successful in much larger optimization
     problems.

  If ADMB works better, why not use it?  You can use the R2admb
package (on R forge) to wrap your ADMB calls in R code, if you
prefer that workflow.

  Ben

As I'm at least partly responsible for CG in optim, and packager of Rcgmin,
I'll recommend
the latter based on experience since it was introduced. I've so far seen no
example where
CG does better than Rcgmin, though I'm sure there are cases to be found.

However, Ben is right that if ADMB does so well (it uses effectively analytic
derivatives), then use it. Rcgmin really wants you to provide gradient code, and
that is
work.

JN


On 07/14/2011 06:00 AM, r-help-request at r-project.org
wrote:
> Message: 85 Date: Wed, 13 Jul 2011 20:20:47 +0000 From: Ben Bolker
<bbolker at gmail.com> To:
> <r-help at stat.math.ethz.ch> Subject: Re: [R] Very slow optim()
Message-ID:
> <loom.20110713T221924-956 at post.gmane.org> Content-Type:
text/plain; charset="utf-8"
> Hamazaki, Hamachan (DFG <toshihide.hamazaki <at> alaska.gov>
writes:
>> > 
>> > Dear list, 
>> > 
>> > I am using optim() function to MLE ~55 parameters, but it is very
slow to
> converge (~ 25 min), whereas I can do
>> > the same in ~1 sec. using ADMB, and ~10 sec using MS EXCEL Solver.
>> > 
>> > Are there any tricks to speed up?
>> > 
>> > Are there better optimization functions? 
>> > 
>   There's absolutely no way to tell without knowing more about your
code.  You
> might try method="CG":
> 
>     Method ?"CG"? is a conjugate gradients method based on that
by
>      Fletcher and Reeves (1964) (but with the option of Polak-Ribiere
>      or Beale-Sorenson updates).  Conjugate gradient methods will
>      generally be more fragile than the BFGS method, but as they do not
>      store a matrix they may be successful in much larger optimization
>      problems.
> 
>   If ADMB works better, why not use it?  You can use the R2admb
> package (on R forge) to wrap your ADMB calls in R code, if you
> prefer that workflow.
> 
>   Ben
> 
> 
>