[R] Maximum log likelihood estimates of the parameters of a nonlinear model.

[Odette Gaston]

Dear all,

Is it possible to generate AIC or something equivalent for nonlinear
model estimated based on maximum log likelihood l in R?
I used nls based on least squares to estimate, and therefore I cannot
assess the quality of models with AIC. nlme seems good for only mixed
models and mine is not mixed models.

res <- nls(y ~ d*(x)^3+a*(x)^2+b*x+c, start=list(a=2, b=1,c=1,d=1), data=d)

If anybody does know a R-function to estimate nonlinear model based on
maximum log likelihood, please let me know.

Thanks for your help in advance!
Odette