Hello, I want to understand how to tell if a model is significant.
For example I have vectX1 and vectY1. I seek first what model is best suited for my vectors and then I want to know if my result is significant. I'am doing like this: model1 <- lm(vectY1 ~ vectX1, data= d), model2 <- nls(vectY1 ~ a*(1-exp(-vectX1/b)) + c, data= d, start = list(a=1, b=3, c=0)) aic1 <- AIC(model1) aic2 <- AIC(model2) if (aic1 < aic2) print("Model1 is better") else print("Model2 is better") for example aic1 < aic2 I'am doing summary(model1) and I have p-value to know if my result is significant. but if aic2 < aic1, so model 2, non linear is better. I'am doing summary(model2) bur there isn't p-value. I read that it is normal. So how can I know if my resultat is significant? I can't use summary.nls(), because, I'm working with mac and it's no possible to install it. Thank you [[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.