[R] glm questions

[David Firth]

On Tuesday, Mar 16, 2004, at 15:15 Europe/London, Rolf Turner wrote:

>
> 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
>

Well, I really did _intend_ GLM when I wrote GLM, meaning the sort of 
theoretical thing that Paul described, involving the presentation to 
(political-science etc) students of the general (linear) exponential 
family.  All that stuff is not needed for a proper understanding of the 
three models mentioned, and certainly those three models are all 
meaningful without it.  Your second paragraph below is one that I 
wholeheartedly agree with though (except that it should be linear 
function of the parameters, not the predictors), and it seems to agree 
also with what I wrote in the second part of the paragraph which you 
quote above (the part that you cut) from my earlier reply.

David

> 	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
> 						rolf at math.unb.ca
>
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