Hi userRs! I am trying to fit some GLM-poisson and neg.binomial. The neg. Binomial model is to account for over-dispersion.
When I fit the poisson model i get: (Dispersion parameter for poisson family taken to be 1) However, if I estimate the dispersion coefficient by means of: sum(residuals(fit,type="pearson")^2)/fit$df.res I obtained 2.4. This is theory means over-dispersion since 2.4>>1. I do not understand what the relation is between (Dispersion parameter for poisson family taken to be 1) and 2.4. In a similar fashion, when i fit the neg. binomial model I obtain: (Dispersion parameter for Negative Binomial(0.1717) family taken to be 1) Whereas the estimation of the dispersion coefficient as stated above is: 1.4 Why Dispersion parameter and my calculation are not the same? Any thoughts will be much appreciate it . -- View this message in context: http://r.789695.n4.nabble.com/GLM-and-Neg-Binomial-models-tp3902173p3902173.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.
