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