1. Substitute the name of the first argument for '.' throughout the expression
2. Evaluate the modified expression using the data argument to the fitted model as the first element of the search list.
The second part is relatively easy. The default method for "with" has body eval(substitute(expr), data, enclos = parent.frame()) and you just change this to eval(substitute(expr), eval(data$call$data), enclos = parent.frame())
So, for example
> fm <- lm(optden ~ carb, Formaldehyde)
> with.lm <- function(data, expr, ...) eval(substitute(expr), eval(data$call$data), enclos = parent.frame())
> with(fm, carb)
[1] 0.1 0.3 0.5 0.6 0.7 0.9
However, I haven't been able to work out a clever way of using substitute to get the first part. I would like to be able to call, e.g.
with(fm, xyplot(resid(.) ~ carb))
and get a plot of resid(fm) ~ Formaldehyde$carb
It is possible to do the first part by deparsing, substituting, and parsing but that's inelegant. Can anyone suggest a more elegant method?
BTW, the example of an lm model is just for illustration. The actual use I have in mind is for lme (now lmer) models. The plot method for the lme class in the nlme package does something very similar to this.
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