Hi there, I'm a PhD student investigating growth patterns in fish. I've been using the minpack.lm package to fit extended von Bertalanffy growth models that include explanatory covariates (temperature and density). I found the nls.lm comand a powerful tool to fit models with a lot of parameters. However, in order to select the best model over the possible candidates (without covariates, with both covariates, or with only one of them) I'd like to compare them based on their AIC criterion. However, it seems that the nls.lm comand doesn't return an AIC, or a Log Likelihood. Does someone have any idea of how I could proceed to get such informations about my models?
Thanks for your help. Best regards, Alan Baudron The University of Aberdeen is a charity registered in Scotland, No SC013683. [[alternative HTML version deleted]] ______________________________________________ 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.