Using the nls function I fit the following model (and some others) to my data. mod1=nls(CLr ~ A-(A-CLi)*exp(-k*d), start = list(A=60,k=0.005)) I would like to rank a set of models using AIC.
I calculated AIC as AIC(mod1) However, it appears to use an incorrect number of parameters (3 instead of 2). Why is this? Additionally, if I calculate AIC using the residuals sum of squares instead of the log likelihood, the AIC values, and resulting delta AICs differ between the two approaches. What am I missing? RSS=231.5;K=2;N=30 N*log(RSS/N)+2*K Help is appreciated, John ______________________________________________ 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.
