On Jun 20, 2011, at 15:08 , albeam wrote:
> Please allow me to clarify my original question. What I really need to be
> able to do it is to take arbitrary functions and evaluate them for arbitrary
> parameter values. I'm doing the optimization myself, so I need to be able to
> take a user's function and evaluate them at the current parameter values
> during my optimization process. So it would look something like this:
>
> opt.fun <- function(user.formula, param.values)
> {
> #--- I would do some optimization here ---#
>
> fitted.values <- eval.fun(user.formula, param.values) ##<---- this is
> what I need
> }
>
> Where fitted.values is a vector of the same size as the x-values in
> user.formula. nls() does this somehow. I could do this easily myself if I
> have the user pass the formula in reverse polish notation, but I was hoping
> there was a more canonical was to do this in R.
>
The canonical way goes something like
eval(user.formula[[3]], #i.e. the RHS
envir = as.list(param.values),
enclos = environment(user.formula))
or maybe enclos = list2env(data, parent = environment(user.formula)) if there's
a data argument.
All untested, of course. If you want us to actually test our suggestions,
follow the instructions
> and provide commented, minimal, self-contained, reproducible code.
--
Peter Dalgaard
Center for Statistics, Copenhagen Business School
Solbjerg Plads 3, 2000 Frederiksberg, Denmark
Phone: (+45)38153501
Email: pd....@cbs.dk Priv: pda...@gmail.com
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