R devel - Mar 2000 - nlm and optional arguments

It would be really nice if nlm took a set of "..." optional arguments
that were passed through to the objective function.  This level of hacking
is probably slightly beyond me: is there a reason it would be technically
difficult/inefficient?  (I have a vague memory that it used to work this
way either in S-PLUS or in some previous version of R, but I could easily
be wrong.)

  Here's a hack in R code that works for me (basically copying the R code
of nlm() but defining a temporary function that passes the optional
arguments to the objective function), but I presume this would be cleaner
and faster if implemented at a lower level ...

nlm2 <- function(f, p, hessian=FALSE, typsize=rep(1,length(p)),
                fscale=1, print.level=0, ndigit=12, gradtol=1e-6,
                stepmax=max(1000 * sqrt(sum((p/typsize)^2)), 1000),
                steptol=1e-6, iterlim=100, check.analyticals=TRUE, ...) {
  tmpf <- function(x) {
    f(x,...)
  }
 
nlm(tmpf,p,hessian=hessian,typsize=typsize,fscale=fscale,print.level=print.level,
     
ndigit=ndigit,gradtol=gradtol,stepmax=stepmax,steptol=steptol,iterlim=iterlim,
      check.analyticals=check.analyticals)
}

  As a matter of general principle, would the R-core folks prefer that
"wishlist" items like this get sent to R-bugs (so they can be kept
better
track of) or not (so they don't clutter up the bugs database) ?

-- 
Ben Bolker                                  bolker@zoo.ufl.edu
Zoology Department, University of Florida   http://www.zoo.ufl.edu/bolker
318 Carr Hall/Box 118525                    tel: (352) 392-5697
Gainesville, FL 32611-8525                  fax: (352) 392-3704

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On Mon, 6 Mar 2000, Ben Bolker wrote:
> 
>   It would be really nice if nlm took a set of "..." optional
arguments
> that were passed through to the objective function.  This level of hacking
> is probably slightly beyond me: is there a reason it would be technically
> difficult/inefficient?  (I have a vague memory that it used to work this
> way either in S-PLUS or in some previous version of R, but I could easily
> be wrong.)
Well, ms and nlminb work that way in S-PLUS, and optimize and optim do in
R, so there is no real problem.
>   Here's a hack in R code that works for me (basically copying the R
code
> of nlm() but defining a temporary function that passes the optional
> arguments to the objective function), but I presume this would be cleaner
> and faster if implemented at a lower level ...
> 
> nlm2 <- function(f, p, hessian=FALSE, typsize=rep(1,length(p)),
>                 fscale=1, print.level=0, ndigit=12, gradtol=1e-6,
>                 stepmax=max(1000 * sqrt(sum((p/typsize)^2)), 1000),
>                 steptol=1e-6, iterlim=100, check.analyticals=TRUE, ...) {
>   tmpf <- function(x) {
>     f(x,...)
>   }
>  
nlm(tmpf,p,hessian=hessian,typsize=typsize,fscale=fscale,print.level=print.level,
>      
ndigit=ndigit,gradtol=gradtol,stepmax=stepmax,steptol=steptol,iterlim=iterlim,
>       check.analyticals=check.analyticals)
> }
One can just put function(x) f(x, ...) as the first argumnet of the
.Internal call.  It can also fairly easily be done internally (but
why bother?)   I'll take a look at this, but why not try optim instead?

>   As a matter of general principle, would the R-core folks prefer that
> "wishlist" items like this get sent to R-bugs (so they can be
kept better
> track of) or not (so they don't clutter up the bugs database) ?
I'll leave that for the R-bugs-master.


-- 
Brian D. Ripley,                  ripley@stats.ox.ac.uk
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  +44 1865 272861 (self)
1 South Parks Road,                     +44 1865 272860 (secr)
Oxford OX1 3TG, UK                Fax:  +44 1865 272595

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