Dispersion in summary.glm() with binomial & poisson link (fwd)

That is why I did not submit a bug report.  The problem is that in
many application areas phi is much greater than one.

The gnlr function in my gnlm library (at
www.luc.ac.be/~jlindsey/rcode.html) will fit quite a variety of
different overdispersed Poisson- and binomial-based distributions
(i.e. phi different from one) using their exact likelihoods.
  Jim

As Bill Venables has kindly pointed out, I was a bit sloppy in the
above: phi here refers to the appropriate overdispersion parameter in
the distribution chosed, negative binomial, beta-binomial, double
exponential, multiplicative Poisson/binomial, etc. For some
distributions, it can be less than one, i.e. underdispersed. Jim
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