On Tue, 24 Jun 2008, Jinsong Zhao wrote:
Another question related with the same code:
r <- c(3,4,4,3,5,4,5,9,8,11,12,13)
n <- rep(15,12)
x <- c(0, 1.1, 1.3, 2.0, 2.2, 2.8, 3.7, 3.9, 4.4, 4.8, 5.9, 6.8)
x <- log10(x)
fr <- function(c, alpha, beta) {
P <- c + (1-c) * pnorm(alpha + beta * x)
P <- pmax(pmin(P,1),0)
-(sum(log(choose(n,r))) + sum(r * log(P)) + sum((n -r)* log(1-P)))
}
fit <- mle((fr), start = list(c =0.2, alpha = 0, beta =0.1), method =
"BFGS")
0 * (-Inf) = NaN.
pnorm(0 + 0*log10(0)) = NaN
See my previous answer.
The above code could terminate normally. However, if ``beta'' set to 0, then
the following error message will appear:
Error in optim(start, f, method = method, hessian = TRUE, ...) :
initial value in 'vmmin' is not finite
I have learn that "drc" package could deal with this situation, it set the
first observation to control, however, I don't find the way to implement it
in the source code, for the code is too complex to me.
Any suggestion? Thanks in advance!
You could always try out your own code piece by piece.
Jinsong
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Brian D. Ripley, [EMAIL PROTECTED]
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and provide commented, minimal, self-contained, reproducible code.
