Hi All, I'm accustomed to performing an ANOVA to aid in choosing between linear models (for example y~x or y~x+x^2), however with different models I can't seem to do it. I'm trying to fit an exponential model of the form ye^(bt).
Below is a code snippet that highlights what I'm trying to do s = rnorm(100, sd = 1, mean=10) s = s + seq(0.1,10,0.1) x = 1:length(s) model.lin = lm(s ~ x) model.poly = lm(s ~x + I(x^2)) model.exp = lm(log(s) ~ x) anova(model.lin, model.poly) #gives the correct outcome anova(model.lin, model.exp) #doesn't. This fails because of the transformation of the response variable. Can anyone give any advice as to how I should proceed - is there a different test to use in this instance, or some way of reversing the transform after the model has been fitted? Any help greatly appreciated!! Richard -- Contendere, Explorare, Invenire, et non Cedere ______________________________________________ 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.
