[R] strange `nls' behaviour

[Katharine Mullen]

I can confirm this behavior on R-2.6.0 but don't have time to look into it
further at the moment.

On Mon, 12 Nov 2007, Joerg van den Hoff wrote:

>
> I initially thought, this should better be posted to r-devel
> but alas! no response. 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.
>