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@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.