Szumiloski, John wrote:
> 
> Dear useRs,
> 
> I have a complicated function to be optimized with optim(), and whose
> parameters are passed to another function within its evaluation.  This
> function allows for the parameters to enter as arguments to various
> probability distribution functions.
> 
> However, I am violating some scoping convention, as somewhere within the
> hierarchy of calls a variable is not visible.  I will give a genericized
> example here.
> 
>> myFxn <- function(parms, Y, phi, <other args>) {<body of function>}
> ### I want to optimize this over its first argument
> 
>>  optim(par=<numeric(>2)>, fn=myFxn, ### end of named args, next are
> all in "..."
>              Y=<data>,  <other args>, 
>              phi=function(r) pnorm(r, mean=parms[2], sd=parms[1])
>              )
> Error in pnorm(r, mean = parms[2], sd = parms[1]) : 
>   object 'parms' not found
>> debugger()        ## options(error=expression(dump.frames())) in
> .RProfile
> Message:  Error in pnorm(r, mean = parms[2], sd = parms[1]) : 
>   object 'parms' not found
> Available environments had calls:
> 1: optim(par = <numeric(>2)>, fn = myFxn, Y=<data>, <other args>, ..
> 2: function (par) 
> 3: fn(par, ...)
> 4: ifelse(<logical vector>, phi(Y), <other stuff within myFxn>
> 5: phi(Y)
> 6: pnorm(r, mean = parms[2], sd = parms[1])
> 
> Now, when using the debugger in environments 1 and 2, I can see the
> value of 'par' correctly.  I cannot access environment 4 as it just
> returns the original error message.  Trying to access environment 3
> gives the (to me) cryptic  'Error in get(.obj, envir =
> dump[[.selection]]) :  argument "..." is missing, with no default' and
> returns to the top level without debugging.  
> 
> I will try to explain to the best of my ability what I think is
> happening here.  Environments 2 and 3 are from the first lines of
> optim(), where it is building an internal function to evaluate the
> candidate parameter values.  When accessing environment 3, it seems like
> when it fills out the "..." argument of fn(), it is passing
> phi=function(r) pnorm(r, mean=parms[2], sd=parms[1]) but upon trying to
> evaluate the variable 'parms', it cannot see it in the search path.
> When actually running the original call, 'parms' is apparently not
> evaluated yet, but is once the pnorm call is hit.  It appears the
> 'parms' variable is being evaluated before the fn(par) is evaluated into
> myFxn(parms=par).   
> 
> A point which is probably, but not certainly, irrelevant:  myFxn() has
> "..." as its final argument, so as to pass tuning arguments to
> integrate().  The function being integrated contains phi(), as well as
> other stuff, of a dummy variable.  The calls in the debugging tree,
> however, are *not* those involving integrate().  
> 
> It would probably be possible to include some
> substitute/eval/as.name/etc. constructions within the function myFxn, in
> order to avoid this problem, but as myFxn already involves numeric
> integrations whose integrand involves the optimized parameters
> themselves, computing on the language at each step of the optimization
> seems like a bad idea.  
> 
> My question: is there a straightforward and efficient way of
> constructing this function and optimizing it with optim(), allowing for
> the argument phi to pass an arbitrary distribution function whose
> parameters are the global ones being optimized?  In particular, in the
> third environment of the debugger tree, is there a way to force the
> fn(par, ...) ----> myFxn(parms=par, ...) evaluation before the "..." get
> evaluated?
> 
> Thanks, John
> 
> John  Szumiloski,  Ph.D.
> 
> Senior Biometrician
> Biometrics Research
> WP53B-120
> Merck Research Laboratories
> P.O. Box 0004
> West Point, PA 19486-0004
> 
>> (215) 652-7346 (PH)
>> (215) 993-1835 (FAX)
>> 
>> 
> #################################################
> ####  obligatory session info
> ####
> ####  Windows XP 2002 sp3, customized by corporate IT
> 
>> version
>                _                                          
> platform       i386-pc-mingw32                            
> arch           i386                                       
> os             mingw32                                    
> system         i386, mingw32                              
> status         Patched                                    
> major          2                                          
> minor          9.2                                        
> year           2009                                       
> month          09                                         
> day            05                                         
> svn rev        49600                                      
> language       R                                          
> version.string R version 2.9.2 Patched (2009-09-05 r49600)
> 
>> search()
>  [1] ".GlobalEnv"        "package:geometry"  "package:datasets"
> "<mylib1>"           "<mylib2>"          
>  [6] "package:VGAM"      "package:stats4"    "package:Design"
> "package:Hmisc"     "package:boot"     
> [11] "package:splines"   "package:MASS"      "package:nnet"
> "package:utils"     "package:stats"    
> [16] "package:graphics"  "package:grDevices" "<mylib3>"
> "<mylib4>"           "<mylib5>"           
> [21] "<mylib6>"              "package:methods"   "Autoloads"
> "package:base"     
> 
> Notice:  This e-mail message, together with any attachme...{{dropped:15}}
> 
> ______________________________________________
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> PLEASE do read the posting guide
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> 
> 


Will the following tweak work for you?  It's not very realistic
but it might solve the problem.

## new version
myFxn <- function(parms, Y,
                  phi=function(r) pnorm(r, mean=parms[2], sd=parms[1]),
                  X) {
  phi(1)
  sum((Y-(parms[1]+parms[2]*X))^2)
}

set.seed(1001)
X = 1:10
Y = 1+2*X+rnorm(10)
  
optim(par=c(1,2), fn=myFxn, 
      Y=Y, X=X)

### original

myFxn2 <- function(parms, Y,
                  phi,
                  X) {
  phi(1)
  sum((Y-(parms[1]+parms[2]*X))^2)
}

set.seed(1001)
X = 1:10
Y = 1+2*X+rnorm(10)
  
optim(par=c(1,2), fn=myFxn2,
      phi = function(r) pnorm(r, mean=parms[2], sd=parms[1]),
      Y=Y, X=X)


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