R Under development (unstable) (2023-12-07 r85661 ucrt) -- "Unsuffered Consequences"
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> ## I am experiencing difficulties with one of my modeling function (bbmle::mle2)
> ## which, like other modeling functions in R, uses match.call() to
> ## retrieve and save the original function call for future use.
> ## I'll describe the problem for bbmle and then show that I can
> ## provoke a similar problem with lm().
> 
> ## ============
> ## PART I: mle2()
> 
>   library(bbmle)
Loading required package: stats4
> 
>   x <- 0:10
>   y <- c(26, 17, 13, 12, 20, 5, 9, 8, 5, 4, 8)
>   d <- data.frame(x,y)
> 
> ## The key is to call the modeling function from within another
> ## function which passes additional arguments via ... 
> 
>   ff <- function(d,...) {
+     mle2(y~dpois(lambda=ymean),start=list(ymean=mean(y)),data=d,...)
+   }
> 
>   ff(d)

Call:
mle2(minuslogl = y ~ dpois(lambda = ymean), start = list(ymean = mean(y)), 
    data = d)

Coefficients:
   ymean 
11.54545 

Log-likelihood: -42.73 
>   try(ff(d,control=list(maxit=1000)))

Call:
mle2(minuslogl = y ~ dpois(lambda = ymean), start = list(ymean = mean(y)), 
    data = d, control = ..1)

Coefficients:
   ymean 
11.54545 

Log-likelihood: -42.73 
> 
> ##   Error in call$control$parscale : 
> ##      object of type 'symbol' is not subsettable
> 
> ## This happens when I try:
> 
> ##  call$control$parscale <- eval.parent(call$control$parscale)
> 
> ## in 'normal' circumstances call$control and call$control$parscale
> ## are either NULL or well-specified ...
> 
> ## Debugging mle2 shows that the results of match.call() are
> 
> ##   mle2(minuslogl = y ~ dpois(lambda = ymean), start = list(ymean = mean(y)), 
> ##       data = d, control = ..1)
> 
> ## ============
> ## PART II: lm()
> 
> ## I can find a similar issue with lm(), although admittedly
> ## I have to work a bit harder/do something a little bit more
> ## obscure.
> 
>   L1 <-  lm(y~1,data=d,tol=1e-6)
>   L1$call
lm(formula = y ~ 1, data = d, tol = 1e-06)
> 
>   ff2 <- function(d,...) {
+     lm(y~1,data=d,...)
+   }
> 
>   tt <- 1e-6
>   L2 <- ff2(d,tol=tt)
>   L2$call
lm(formula = y ~ 1, data = d, tol = ..1)
> 
>   try(update(L2,.~.+x))
Error in lm.fit(x, y, offset = offset, singular.ok = singular.ok, ...) : 
  ..1 used in an incorrect context, no ... to look in
> 
> ## Error in lm.fit(x, y, offset = offset, singular.ok = singular.ok, ...) : 
> ##   ..1 used in an incorrect context, no ... to look in
> 
>  ## similar issue in curve3d().  How does curve() work?
> 
> 
> 
> proc.time()
   user  system elapsed 
   1.12    0.21    1.34