Good afternoon everybody,
I'm using optimization routines like optimix or nlminb to optimize the
parameters of my dispersal curves which are "working" with different
kernels :
/anlb2002z1b <- nlminb(c(0.5,2), objective=LogLiketot,lower=c(0,0),
upper=c(1,200))/
where /LogLiketot/ contains my dispersal kernel parameters and
/(0.5,2)/, an exemple of starting point to estimate these parameters.
/anlb2002z1b/ returns me different values, including the AIC.
On the same data, I'm comparing 3 dispersal kernels, exponential kernel
(one parameter), exponential-power kernel (two-parameters) and geometric
kernel (two-parameters).
Is there a way, in R, to compare these dispersal kernels on the base of
their AIC to find the best fitting one ? A Likelihood ratio test works
only for nested models ...
Thanks in advance for your help.
Diane.
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