>>>>> "DM" == Duncan Murdoch <[EMAIL PROTECTED]>
>>>>> 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
- 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...
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@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@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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