Hello,
I am comparing models made with nlme functions and non-nlme functions, based
on Akaike's AIC. The AIC values I get for exactly the same model formulation
--for example a linear model with no random effects fit with gls and lm,
respectively-- do not fit, although the values of the four model parameters
are exactly the same. For example:
m1 <- gls(height ~ age, data = Loblolly)
m2 <- lm(height ~ age, data = Loblolly)
m1$coefficients
(Intercept) age
-1.312396 2.590523
m2$coefficients
(Intercept) age
-1.312396 2.590523
But then:
AIC(m1)
[1] 428.9243
AIC(m2)
[1] 423.9153
I am trying to compare between more complex models, i.e. different ways of
incorporating spatial self-correlation, and this issue with the AIC is
really making me silly!
Thanks,
S. Begueria
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