RE: Generalized linear models

From: Patrick Cordue <>
Date: Wed, 18 Feb 2009 19:28:13 +1300

Hi Chris,

I was thinking that the family and the link were available, e.g., for a
particular dataset the "best model" is found to be Gaussian with a log link,
say log(E(Y)) = a + bx. My question is what more can be said about how the
error combines with "a +bx", i.e., is the glm compatible with a model: Y =
exp(a + bx) + e where e ~ N(0,s^2), and is it compatible with Y = exp(a + b)
* e where e ~ N(1, s^2). Now, I think I know the answer to that and I can
check other specific examples such as gamma with a log link etc. But, has
someone already done this (i.e., additive vs multiplicative errors) for
various families and link functions?


Patrick Cordue
Innovative Solutions Ltd
-----Original Message-----
From: Chris Lloyd []
Sent: Wednesday, February 18, 2009 5:41 PM
To: Patrick Cordue
Subject: RE: Generalized linear models
It is supposed to be linear on the link scale. If they do not specify
the link then it is not true that "The model is clearly described in
terms of variables and structure for the mean response."
Professor Chris J. Lloyd
Associate Dean of Research
Melbourne Business School
Ph: 613 -9349-8228
P.S. You can view my selected research and sign up for notification of
new work at:
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Personal Homepage:
-----Original Message-----
[] On Behalf Of Patrick Cordue
Sent: Wednesday, 18 February 2009 3:23 PM
Subject: Generalized linear models
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
Innovative Solutions Ltd
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Received on Wed Feb 18 2009 - 16:28:19 EST

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