[R] nls problem

[joerg van den hoff]

hi list,

used versions: 2.12.1 and 2.14.0 under ubuntu and macosx.

I recently stumbled over a problem with `nls', which occurs if the model  
is not specified explicitly but via an evaluation of a 'call' object.  
simple example:

8<--------------------------------------------------------------------------------------

nlsProblem <- function (len = 5) {
#=======================================================================
    # purpose: to demonstrate an apparent problem with `nls' which occurs,
    # if the model is specified by passing th lhs as an evaled 'call'
    # object.  The problem is related to the way `nls' tries to compute
    # its internal variable `varIndex' which rests on the assumption that
    # the dependent ("y") and, possibly, the independent ("x") variable
    # are identified by having a length equal to the `nls' variable
    # `respLength'. the problem arises when there are `varNames'
    # components accidentally having this length, too.

    # in the present example, setting the number of data points to
    # len=2 triggers the error since the `call' object `fifu' has this
    # length, too and `nls' constructs an erroneous `mf$formula' internally.
#=======================================================================
    #generate some data
    x <- seq(0, 4, len = len)
    y <- exp(-x)
    y <- rnorm(y, y, .001*y)
    data <- list(x = x, y = y)

    #define suitable model
    model <- y ~ exp(-k*x)
    fifu  <- model[[3]]

    #this fit is fine:
    fit1 <- nls(model, data = data, start = c(k = 1))
    print(summary(fit1))

    #this fit crashes `nls' if len = 2:
    fit2 <- nls(y ~ eval(fifu), data = data, start = c(k = 1))
    print(summary(fit2))
}

8<--------------------------------------------------------------------------------------

to see the problem call `nlsProblem(2)'.

as explained in the above comments in the example function, I tracked it  
down to the way
`nls' identifies x and y in the model expression. the problem surfaces in  
the line

         varIndex <- n%%respLength == 0

(line 70 in the function listing from within R) which, in the case of  
`fit2' in the above
example always returns a single TRUE index as long as `len != 2' (which  
seems fine for the
further processing) but returns a TRUE value for the index of `fifu' as  
well if `len == 2'.

question1: I'm rather sure it worked about 6 months ago with (ca.) 2.11.x  
under ubuntu. have there been changes in this area?
question2: is something like the `fit2' line in the example expected to  
work or not?
qeustion3: if it is not expected to work, should not the manpage include a  
corresponding caveat?
question4: is there a a substitute/workaround for the `fit2' line which  
still allows to specify the rhs of the model via a variable instead of a  
constant (explicit) expression or function call?

the above  example is of course construed but in my use case I actually  
need this sort of thing. is there any chance that
the way `nls' analyzes its `model' argument can be changed to parse the  
`eval(fifu)' construct correctly in all cases?

since I'm currently not subscribed to the list I'd appreciate if responses  
could be Cc'ed to me directly.

thanks in advance,

joerg