Can anyone explain to me why the AIC values are so different when using glm.nb and glm with a negative.binomial family, from the MASS library? I'm using R 1.8.1 with Mac 0S 10.3.4.
>library(MASS) > dfr <- data.frame(c=rnbinom(100,size=2,mu=rep(c(10,20,100,1000),rep(25,4))), + f=factor(rep(seq(1,4),rep(25,4)))) > AIC(nb1 <- glm.nb(c~f, data=dfr)) [1] 1047 > AIC(glm(c~f, family=negative.binomial(nb1$theta), data=dfr)) [1] -431804 Actually, the difference is already apparent with the function logLik, but I still would like to understand the difference in what is calculated in the two instances. Thank you, in advance. ____________________ Ken Knoblauch Inserm U 371 Cerveau et Vision 18 avenue du Doyen Lepine 69675 Bron cedex France tel: +33 (0)4 72 91 34 77 fax: +33 (0)4 72 91 34 61 portable: 06 84 10 64 10 ______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
