[R] Negative Binomial Regression - glm.nb

[Prof Brian Ripley]

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.

> Thank you very much for your answer in advance!
>
> 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)
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