There is -xtnbreg-, look it up and see if it does the job you need.
If it does not, I would expect that with trial and a lot of errors,
you can squeeze something of a kind from -gllamm- (which is a terrific
piece of software for lots of modeling issues). The basic outline is
to have a 2-point latent variable to model the mixture giving rise to
zero-inflated Poisson; and then use Poisson link for one part of the
mixture, and binomial link with the other. I am thinking aloud there,
I don't know if it is really feasible, so look up the book somebody
just mentioned by Sophia Rabe-Hesketh and Anders Skrondal.
On 3/11/07, Dr. Stephen Rothenberg <srothenberg@mda.cinvestav.mx> wrote:

I'm trying to determine the parameters of a distribution of a time-series of
yearly number of disease cases over a 33 year period. The series has many
zero values, and the variance is much larger than the mean (var=13.6,
mean=1.6). Since the data is taken from one city over a number of years,
serial correlation may be expected.
My goal is to determine the probability of x number or greater cases in any
given year, given the entire series.
I'm looking for something like -nbfit- for correlated data. Or -nbreg-
(with independent variables, like year) for correlated data.

--
Stas Kolenikov
http://stas.kolenikov.name
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