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, rip...@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
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