[R] function in nls argument

From: Fernando Moyano <nanomoyano_at_yahoo.com>
Date: Wed, 07 May 2008 08:40:36 -0700 (PDT)

I define a function "optim.fun" and want as output the sum of squared errors between predicted and measured values, as follows:

optim.fun <- function (ST04, SM08b, ch2no, a, b, d, E)

```        {
predR <-

(a*SM08b^I(2)+b*SM08b+d)*exp(E*((1/(283.15-227.13))-(1/(ST04+273.15-227.13))))

abserr <- abs(ch2no-predR)
qnum <- quantile(abserr, probs=0.95, na.rm=T)

is.na(abserr) <- (abserr > qnum)
errsq <- sum(abserr^2, na.rm=T)
errsq
}

```

Then I want to optimize parameters a,b,d and E as to minimize the function output with the following:

optim.model<-nls(nulldat ~ optim.fun(ST04, SM08b, ch2no, a, b, d, E), data=tower,
start=list(a=-0.003,b=0.13,d=0.50, E=400), na.action = na.exclude )

were nulldat=0
At this point I get the following error message:

Error in qr.default(.swts * attr(rhs, "gradient")) :   NA/NaN/Inf in foreign function call (arg 1) Warning messages:
1: In if (na.rm) x <- x[!is.na(x)] else if
(any(is.na(x))) stop("missing values and NaN's not
allowed if 'na.rm' is FALSE") ... :
the condition has length > 1 and only the first element will be used
(this warning is repeated 12 times)

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