From: Patrick Cordue <patrick.cordue_at_isl-solutions.co.nz>

Date: Wed, 18 Feb 2009 17:22:49 +1300

Date: Wed, 18 Feb 2009 17:22:49 +1300

Hi All,

For any given model it is usually straightforward to check if it satisfies

the assumption of a GLM (and if it does, one can use glm() in R, for

example, with an appropriate distribution family and link function, to

obtain estimates of the coefficients, etc).

However, given a dataset, which is analyzed using glm(), one may arrive at a

"best model" which uses a particular family and link function (and a set of

explanatory variables). The model is clearly described in terms of variables

and structure for the mean response, and the distribution of the response

variables is explicit, but the "exact" form of the error structure is not

explicit (e.g., are the errors additive or multiplicative?, e.g., Y = a + bx

+ e, or Y = (a + bx) * e, both can have E(Y) = a + bx). I assume that some

general results are available - can anyone point me to, for example, an

online list of implicit error structure given the currently implemented

families and link functions in R. Any comments, links, or references

appreciated. TIA.

-- ----- Patrick Cordue Director Innovative Solutions Ltd www.isl-solutions.co.nz ---- FOR INFORMATION ABOUT "ANZSTAT", INCLUDING UNSUBSCRIBING, PLEASE VISIT http://www.maths.uq.edu.au/anzstat/Received on Wed Feb 18 2009 - 14:22:55 EST

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