Generalized linear models

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

This archive was generated by hypermail 2.2.0 : Thu Feb 26 2009 - 11:40:40 EST