[R] AIC in bestglm, glm, and lm - why do they differ?

[dmgillis at istar.ca]

I recently found the ?bestglm? package while trolling CRAN for a  
function to save some keystrokes with simple (k<10) nested models.  I  
am interested in using the best of several nested linear models which  
I have explored using lm(), glm() and now bestglm().  When I compare  
the AIC values for the ?best? candidate model I get the same AIC  
values with lm() and glm() but a different AIC (and likelihood) value  
from bestglm().  Is this the result of some difference in likelihood  
calculation that I am missing in reviewing the documentation and help  
files? I can provide code if there is interest in looking into this,  
otherwise I will continue to assemble my tables the long way with  
glm() and lm(), though the options and potential of the bestglm()  
package has me very interested.

Cheers, Darren Gillis

Biological Sciences
University of Manitoba
Winnipeg, MB