subject:"\[R\] over\-estimation Negative Binomial models"

Re: [R] over-estimation Negative Binomial models

2011-10-18 Thread D_Tomas

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(lo

Re: [R] over-estimation Negative Binomial models

2011-10-18 Thread Ben Bolker

D_Tomas hotmail.com> writes: > I have fitted a Negative Binomial model (glm.nb) and a Poisson model (glm > family=poisson) to some count data. Both have the same explanatory variables > & dataset > > When I call sum(fitted(model.poisson)) for my GLM-Poisson model, I obtain > exactly the same n

[R] over-estimation Negative Binomial models

2011-10-17 Thread D_Tomas

Hi! I have fitted a Negative Binomial model (glm.nb) and a Poisson model (glm family=poisson) to some count data. Both have the same explanatory variables & dataset When I call sum(fitted(model.poisson)) for my GLM-Poisson model, I obtain exactly the same number of counts as my data. However,