Antje Niederlein <niederlein-rstat <at> yahoo.de> writes:
>
> A few day ago, I was looking for an answer to my question but didn't
> get one. Anybody who can help now?
>
> Hello,
>
> I tried to use mle to fit a distribution(zero-inflated negbin for
> count data). My call is very simple:
>
I will point out that this is one of the reasons I wrote mle2
(in the bbmle package), which differs from mle in taking an explicit
'data' argument. I *think* the following does what you want (although
I admit I haven't looked at the output closely):
library(plyr)
library(bbmle)
lambda.data <- runif(10,0.5,10)
ll <- function(lambda = 1) {
cat("x in ll()",x,"\n")
y.fit <- dpois(x, lambda)
sum( (y - y.fit)^2 )
}
lapply(1:10, FUN = function(x){
raw.data <- rpois(100,lambda.data[x])
freqTab <- count(raw.data)
x <- freqTab$x
y <- freqTab$freq / sum(freqTab$freq)
cat("x in lapply", x,"\n")
fit <- mle2(ll,data=data.frame(x,y))
coef(fit)
})
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