I am trying to model counts data from three different sites where the number of zeros
differs significantly from one sight to another and also the counts gets bigger in
site with few number of zeros considerably, meaning that the k's are different. In my
model I am including about 10 covariates to start with, and I have beed attempting to
fit a NEGATIVE BINOMIAL MODEL. The problem is the function glm.nb neither
glm(formula,family=negative.binomial(k),data) work when I have all covariates in the
model. But when we fit only intercept or few covariates, the algorithm converge. I
also fitted the logistic binary (binomial) for the all three sites using glm with all
covariates and there was no problem. I also fitted the lognormal (counts) model for
one of the site using glm and this worked fine. I have tried to go through the help
files in R and Venables & Ripley 4th Edition but I couldn�t find appropriate solution
for my problem.
Please could you give me idea of how to go about it?
Thanks
BPM
Attached is the part of the out put:
fit <- glm.nb PFD~SEX+RES+TRAV+TRAVH+HEIGHT+WEIG+MUA+TEM+FEVV+VOM+HEA....,data=data)
Error: NA/NaN/Inf in foreign function call (arg 1)
In addition: Warning message:
iteration limit reached in: theta.ml(Y, mu, n, limit = control$maxit, trace =
control$trace >
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