Hello r-help, As the title suggests, I'm attempting to fit a negative binomial GLM with a fixed dispersion parameter.
Both glm.nb() and glm(..., family=negative.binomial(theta, ...)) (using MASS) do not appear to allow this; upon specifying a value for theta, each then proceeds to re-estimate it. Both ML and moment estimators of theta in my situation are heavily biased, so I'm using a specific quasilikelihood approach (adjusted profile likelihood, Lee & Nelder '98) to estimate it in advance. Passing glm.nb() a value of theta = 0.4907 results in > model1 <- glm(number ~ as.factor(stratyear), family=negative.binomial(theta=nbk.est, link="identity")) ... (Dispersion parameter for Negative Binomial(0.4907) family taken to be 0.819622) upon the model being fitted. Other posts on r-help have suggested using negbin() in package aod, but I'm curious as to whether or not a fixed-theta NB GLM can be implemented in either the standard glm() framework or using glm.nb()? Thanks, -- jared tobin student, fisheries and oceans canada [EMAIL PROTECTED] ______________________________________________ [email protected] 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.
