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 ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
