[R] generating overdispersed poisson & negative binomial data
ben at zoo.ufl.edu
Mon Jun 10 03:46:34 CEST 2002
I think part of the reason that people use quasi-likelihoods in the
first place is that they can't think of simple models that give them the
desired scaling ... if you find definitions, e.g. of compounded
or generalized distributions that give var=c*mean, I'd be interested. In
the meantime can you do something with compounding distributions?
(Unfortunately the only thing that springs to mind is e.g. Poisson with
gamma-distributed rate, which gives negative-binomial in any case, not
constant var*mean; Poisson+log-normal rate would be slightly more
flexible but? if my moment-generating-functions algebra was less rusty I
might play around with it ...) I also might look in Johnson & Kotz, which
I don't have with me.
On Thu, 6 Jun 2002, Mike Lonergan wrote:
> I would like to try a simple parametric bootstrap, but unfortunately
> (stupidly?) my models are "overdispersed" gams & glms.
> I'm hoping for a function that generates overdispersed poisson or negative
> binomial data with a given mean, scale (& shape parameter).
> The loose definition I'm using is overdispersed poisson produces integer
> values with variance=const*mean & "looks like" a poisson, & simly for
> overdispersed negative binomial - I am aware that odnb is a strange thing to
> Maybe the "integer-valued" bit of my definition is unnecessary, which would
> mean a simple scaling would suffice, but I don't know enough to decide on
> this without testing.
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