Hi there,
I'm pretty new to the field of fitting (anything). I try to fit a
distribution with mle, because my real data seems to follow a
zero-inflated poisson distribution. So far, I tried a simple example
to see whether I understand how to do it or not:
# example count data
x <- 0:10
y <- dpois(x, lambda = 1.4)
# zero-inflated poisson
zip <- function(x, lambda, prop) {
(1 - prop)*dpois(x,0) + prop*dpois(x,lambda)
}
ll <- function(lambda = 2, prop = 0.9) {
y.fit <- zip(x, lambda, prop)
sum( (y - y.fit)^2 )
}
fit <- mle(ll)
So far, so good. The result gives me
lambda prop
1.4 1.0
which is pretty nice.
But what goes wrong if I want to display confidence intervals? I get a
lot of warnings but I simply don't know why...
confint(fit)
Has it something to do with constraints for my parameters (lambda
should be > than zero and prop should range from 0 to 1)? Do I have to
put it into the ll-function?
Is there any general comment on what I'm doing?
Antje
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