David Firth wrote (in response to a question from Paul Johnson):
> On the more general point: yes, if all that students need to know is
> OLS, Poisson rate models and logistic regression, then GLM is overkill.
I couldn't agree less. The glm (not GLM!) framework gives a
coherence to the structure and changes a collection of ad hoc
(and thereby essentially meaningless cook-book) techniques
into a single meaningful technique:
A parameter (the mean) of a distribution is a transformation
of a linear function of some predictors. One seeks to
estimate the linear coefficients via maximum likelihood. In
a broad array of circumstances the maximization can be
carried out by the glm() function (using iteratively
reweighted least squares). The process is quick and
efficient and the notation is about as transparent as can be
imagined.
cheers,
Rolf Turner
[EMAIL PROTECTED]
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