[R] GLM for Beta distribution

[Jim Lindsey]

> On Wed, 19 Feb 2003, Sharon Kuhlmann-Berenzon wrote:
> 
> >
> > Hi R-help,
> >
> > Is there such a thing as a function in R for fitting a GLM where the
> > response is distributed as a Beta distribution?
> >
> > In my case, the response variable is a percentage ([0,1] and continuous).
> >
> > The current glm() function in R doesn't include the Beta distribution.
> >
> 
> That's because they aren't generalised linear models.
> 
> Two simple possibilities
> 
>  - use the quasibinomial variance and an appropriate link such as logit in
> glm -- there's an example in McCullagh & Nelder that tries this (though
> they decide in the end that it doesn't fit their data very well)
> 
>  - Take logits and model with linear regression: a lot of beta
> distributions are fairly similar to logit-normal distributions.

A third simple possibility: my gnlr function in my gnlm library, which
fits linear and nonlinear regression models with a beta distribution.
www.luc.ac.be/~jlindsey/rcode.html
  Jim

> 
> Or you could write down the loglikelihood and use nlm() or optim() to
> maximise it.
> 
> 	-thomas
> 
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