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")
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!
Jinsong
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