Message-ID: <1318941025236-3915162.post@n4.nabble.com>
Date: 2011-10-18T12:30:25Z
From: D_Tomas
Subject: over-estimation Negative Binomial models
In-Reply-To: <loom.20111018T140951-387@post.gmane.org>
Ben,
this is a continuation of the query i posted on:
http://r.789695.n4.nabble.com/GLM-and-Neg-Binomial-models-td3902173.html
I cannot give you a direct example (big dataset) of what i did aside from
what i have written:
fitpoisson <- glm((RESPONSE) ~ A + B +
offset(log(LENGTH)) + offset(log(LENGTH_OBSERVATION)),family="poisson",data=
dataset)
fitneg <- glm.nb((RESPONSE) ~ A + B +
offset(log(LENGTH)) + offset(log(LENGTH_OBSERVATION)),data= dataset)
> sum(fitted(fitpoisson))
[1] 373
> sum(fitted(fitneg))
[1] 514
Observed data is 373....
Any thoughts?
tomas
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