[R] AIC, glm, lognormal distribution

[Benjamin M. Osborne]

I'm attempting to do model selection with AIC, using a glm and a lognormal
distribution, but:

fit1<-glm(BA~Year,data=pdat.sp1.65.04, family=gaussian(link="log"))

## gives the same result as either of the following:
fit1<-glm(BA~Year,data=pdat.sp1.65.04, family=gaussian)
fit1<-lm(BA~Year,data=pdat.sp1.65.04)

fit1
#Coefficients:
#(Intercept)     Year2004
#    -1.6341      -0.2741

#Degrees of Freedom: 84 Total (i.e. Null);  83 Residual
#Null Deviance:      1.521
#Residual Deviance: 1.476        AIC: -97.31


fit1<-glm(BA~Year,data=pdat.sp1.65.04, family=quasi(link="log"))
# also gives the same result but returns AIC: NA


## Is it possible to model a lognormal distribution without having to transform
## the data themselves?  (i.e.:

fit1<-lm(log(BA)~Year,data=pdat.sp1.65.04)



Thanks in advance,
Ben Osborne

--
Botany Department
University of Vermont
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benjamin.osborne at uvm.edu
phone: 802-656-0297
fax: 802-656-0440