[R] strange `nls' behaviour
Joerg van den Hoff
j.van_den_hoff at fzd.de
Mon Nov 12 16:18:26 CET 2007
On Mon, Nov 12, 2007 at 03:25:38PM +0100, Martin Maechler wrote:
> >>>>> "DM" == Duncan Murdoch <murdoch at stats.uwo.ca>
> >>>>> on Mon, 12 Nov 2007 07:36:34 -0500 writes:
>
> DM> On 11/12/2007 6:51 AM, Joerg van den Hoff wrote:
> >> I initially thought, this should better be posted to r-devel
> >> but alas! no response.
>
> DM> I think the reason there was no response is that your example is too
> DM> complicated. You're doing a lot of strange things (fitfunc as a result
> DM> of deriv, using as.name, as.call, as.formula, etc.) You should simplify
> DM> it down to isolate the bug. Thats a lot of work, but you're the one in
> DM> the best position to do it. I'd say there's at least an even chance
> DM> that the bug is in your code rather than in nls().
>
> yes.. and.. no :
> - His code is quite peculiar, but I think only slightly too complicated
thank's for this response. I just tried to give an easier
example in response to duncan's mail.
>
> - one could argue that the bug is in Joerg's thinking that
> something like
> nls(y ~ eval(fitfunc), ....)
>
> should be working at all.
> But then he had found by experiment that it (accidentally I d'say)
> does work in many cases.
>
> DM> And 2.5.0 *is* ancient; please confirm the bug exists in R-patched if it
> DM> turns out to be an R bug.
>
> You are right, but indeed (as has Kate just said) it *does*
> exist in current R versions.
>
> I agree that the behavior of nls() here is sub-optimal.
> It *should* be consistent, i.e. work the same for n=4,5,6,..
>
> I had spent about an hour after Joerg's R-devel posting,
> and found to be too busy with more urgent matters --
> unfortunately forgetting to give *some* feedback about my findings.
>
> It may well be that we find that nls() should give an
> (intelligible) error message in such eval() cases - rather than
> only in one case...
well, if at all possible, it would _really_ be nice to have
the opportunity to pass `eval' constructs throught the
`model' argument to `nls'. I'm far from understanding what
actually is going on in `model.frame', but if it parses the
thing correctly ("accidentally" or not) except in one
special case, is'nt there a clean way to "repair" the
special case? in my application I found the ability to use
`eval' constructs here really helpful. at least I did not
find another way to be able to use `deriv' information _and_
allow the user to use arbitrary symbols in specifying the
model formula. at least I'd prefer the present situation of
"works nearly always" to a consistent "works never".
joerg
>
> Martin Maechler
>
>
> DM> Duncan Murdoch
>
>
>
>
> DM> so I try it here. sory for the
> >> lengthy explanation but it seems unavoidable. to quickly see
> >> the problem simply copy the litte example below and execute
> >>
> >> f(n=5)
> >>
> >> which crashes. called with n != 5 (and of course n>3 since
> >> there are 3 parameters in the model...) everything is as it
> >> should be.
> >>
> >> in detail:
> >> I stumbled over the follwing _very_ strange behaviour/error
> >> when using `nls' which I'm tempted (despite the implied
> >> "dangers") to call a bug:
> >>
> >> I've written a driver for `nls' which allows specifying the
> >> model and the data vectors using arbitrary symbols. these
> >> are internally mapped to consistent names, which poses a
> >> slight complication when using `deriv' to provide analytic
> >> derivatives. the following fragment gives the idea:
> >>
> >> #-----------------------------------------
> >> f <- function(n = 4) {
> >>
> >> x <- seq(0, 5, length = n)
> >>
> >> y <- 2 * exp(-1*x) + 2;
> >> y <- rnorm(y,y, 0.01*y)
> >>
> >> model <- y ~ a * exp (-b*x) + c
> >>
> >> fitfunc <- deriv(model[[3]], c("a", "b", "c"), c("a", "b", "c", "x"))
> >>
> >> #"standard" call of nls:
> >> res1 <- nls(y ~ fitfunc(a, b, c, x), start = c(a=1, b=1, c=1))
> >>
> >> call.fitfunc <-
> >> c(list(fitfunc), as.name("a"), as.name("b"), as.name("c"), as.name("x"))
> >> call.fitfunc <- as.call(call.fitfunc)
> >> frml <- as.formula("y ~ eval(call.fitfunc)")
> >>
> >> #"computed" call of nls:
> >> res2 <- nls(frml, start = c(a=1, b=1, c=1))
> >>
> >> list(res1 = res1, res2 = res2)
> >> }
> >> #-----------------------------------------
> >>
> >> the argument `n' defines the number of (simulated) data
> >> points x/y which are going to be fitted by some model ( here
> >> y ~ a*exp(-b*x)+c )
> >>
> >> the first call to `nls' is the standard way of calling `nls'
> >> when knowing all the variable and parameter names.
> >>
> >> the second call (yielding `res2') uses a constructed formula
> >> in `frml' (which in this example is of course not necessary,
> >> but in the general case 'a,b,c,x,y' are not a priori known
> >> names).
> >>
> >> now, here is the problem: the call
> >>
> >> f(4)
> >>
> >> runs fine/consistently, as does every call with n > 5.
> >>
> >> BUT: for n = 5 (i.e. issuing f(5))
> >>
> >> the second fit leads to the error message:
> >>
> >> "Error in model.frame(formula, rownames, variables, varnames, extras, extranames, :
> >> invalid type (language) for variable 'call.fitfunc'"
> >>
> >> I cornered this to a spot in `nls' where a model frame is
> >> constructed in variable `mf'. the parsing/constructing here
> >> seems simply to be messed up for n = 5: `call.fitfunc' is
> >> interpreted as variable.
> >>
> >> I, moreover, empirically noted that the problem occurs when
> >> the total number of parameters plus dependent/independent
> >> variables equals the number of data points (in the present
> >> example a,b,c,x,y).
> >>
> >> so it is not the 'magic' number of 5 but rather the identity
> >> of data vector length and number of parameters+variables in
> >> the model which leads to the problem.
> >>
> >> this is with 2.5.0 (which hopefully is not considered
> >> ancient) and MacOSX 10.4.10.
> >>
> >> any ideas?
> >>
> >> thanks
> >>
> >> joerg
> >>
> >> ______________________________________________
> >> R-help at r-project.org mailing list
> >> https://stat.ethz.ch/mailman/listinfo/r-help
> >> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> >> and provide commented, minimal, self-contained, reproducible code.
>
> DM> ______________________________________________
> DM> R-help at r-project.org mailing list
> DM> https://stat.ethz.ch/mailman/listinfo/r-help
> DM> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> DM> and provide commented, minimal, self-contained, reproducible code.
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