# [R] Negative Binomial Regression - glm.nb

Prof Brian Ripley ripley at stats.ox.ac.uk
Thu Feb 28 08:41:24 CET 2013

On 28/02/2013 07:27, Martin Spindler wrote:
> Dear all,
>
> I would like to ask, if there is a way to make the variance / dispersion parameter $\theta$ (referring to MASS, 4th edition, p. 206) in the function glm.nb dependent on the data, e.g. $1/ \theta = exp(x \beta)$ and to estimate the parameter vector $\beta$ additionally.

That is no longer a glm, so no.

> If this is not possible with glm.nb, is there another function / package which might do that?

You can maximize the likelihood directly.  How to do that is exemplified
in the optimization chapter of MASS.

>
> Best,
>
> Martin

--
Brian D. Ripley,                  ripley at stats.ox.ac.uk
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  +44 1865 272861 (self)
1 South Parks Road,                     +44 1865 272866 (PA)
Oxford OX1 3TG, UK                Fax:  +44 1865 272595