[Rd] environment confusion

[Ben Bolker]

  I'm in a bit beyond my depth with environments and such.

  The environment of a particular function, which I've set
so it should have the things it needs, seems to be getting
"lost" at some point during a call sequence.
   It's hard to come up with a _simple_ reproducible
example, although if anyone's sufficiently interested I
can post the package somewhere -- with the package installed,
it's only a few steps to reproduce the example.

  I end up, deep in the process of trying to compute
a likelihood profile, with the following situation:
I want to evaluate "call":

call

mle2(minuslogl = function (lmu = NULL, ltheta = NULL)
{
    if (!is.null(parameters)) {
        pars <- unlist(as.list(match.call())[-1])
        for (i in seq(along = parameters)) {
            assign(vars[i], mmats[[i]] %*% pars[vpos[[i]]])
        }
    }
    arglist1 <- lapply(arglist1, eval, envir = data, enclos =
sys.frame(sys.nframe()))
    r <- -sum(do.call(ddistn, arglist1))
    r
}, start = list(lmu = -2.16316747342067, ltheta = 2.30970721353114),
    fixed = list(lmu = -2.18543734742826))

  The function appears to have the right stuff in its
environment:

Browse[1]> ls(envir=environment(call$minuslogl))
[1] "arglist1" "ddistn"   "mmats"    "vars"     "vpos"

   But evaluating the call, even with the environment
set to the environment of the internal function, doesn't
seem to work

Browse[1]> eval(call,envir=environment(call$minuslogl))
Error during wrapup: object "arglist1" not found

  The full stack looks like this:

> profile(m0f,skiperrs=FALSE)
Error in is.vector(X) : object "arglist1" not found

Enter a frame number, or 0 to exit

 1: profile(m0f, skiperrs = FALSE)
 2: profile(m0f, skiperrs = FALSE)
 3: .local(fitted, ...)
 4: onestep(step)
 5: eval.parent(call, 2)
 6: eval(expr, p)
 7: eval(expr, envir, enclos)
 8: mle2(minuslogl = function (lmu = NULL, ltheta = NULL)
 9: optim(start, objectivefunction, method = method, hessian = TRUE, ...)
10: function (par)
11: fn(par, ...)
12: do.call("minuslogl", args, envir = environment(minuslogl))
13: minuslogl(ltheta = 2.30970721353114, lmu = -2.18543734742826)
14: lapply(arglist1, eval, envir = data, enclos = sys.frame(sys.nframe()))
15: is.vector(X)

Selection:

  Anyone have any ideas/directions/leading questions?

  cheers
    Ben Bolker



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