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 -- View this message in context: http://r.789695.n4.nabble.com/over-estimation-Negative-Binomial-models-tp3912692p3915162.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
