R help - Jun 2004 - AIC in glm.nb and glm(...family=negative.binomial(.))

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
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France
tel: +33 (0)4 72 91 34 77
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portable: 06 84 10 64 10

You have the code, so take a look for youself.  There's an error in the 
aic formula in negative.binomial (and neg.bin)

On Tue, 15 Jun 2004, Ken Knoblauch wrote:
> 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.
-- 
Brian D. Ripley,                  ripley at stats.ox.ac.uk
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  +44 1865 272861 (self)
1 South Parks Road,                     +44 1865 272866 (PA)
Oxford OX1 3TG, UK                Fax:  +44 1865 272595