[R] asymptotic convergence intervall for poisson regression

[soxx]

Hello!

The following code is an implementation of a Poisson regression. It
generates some data-samples and computes the beta values with the negative
log likelihood function.
Now, my task is to compute the asymptotic convergence intervalls for the
values of beta but I dont know how to implement this function - this topic
is not in my lecture notes.

I hope someone can help me.

 > library(Bhat)

 > # generate new data

 > dose <- c(rep(0,50), rep(1,50), rep(5,50), rep(10,50))
 > data <- cbind(dose, rpois(200,2*(1+(10-dose)
                *.5*(1-(10-dose)*0.05))))
 > data
 > lambda <- function(dose)
 > {
 >         2*(1+(10 - dose) * .5 * (1-(10-dose)*0.05))
 > }

 > plot(c(0:10),lambda(c(0:10)))
 > # estimated count of fits - dose 0:10
 > plot (data[,1] + rnorm(200, mean=0, sd=0.15), data[,2])

 > # Likelihood - function

 > negloglike <- function(beta)
 > {
 >         ds <- data[,1]
 >         x <- data[,2]

 >         lambda <- beta[1] * (1 + ( 10 - ds )
                * beta[2] * (1 - (10 - ds) * beta[3]))
 >         return(sum(lambda - x * log(lambda)))
 > }

 > beta <- list(label = c("beta1","beta2","beta3"),
        est=c(2.5,0.5,0.1), low=c(1,0,0),upp=c(3,2,2))
 > result <- dfp(beta,f=negloglike)
 > result 


Kind regards

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