Dear mr Joris Meys I would like to know, where to find this formulas in books or articles. # possibility 1 R2 <- cor(y,predict(mod))^2
# possibility 2 R2 <- 1 - ( sum( (y-predict(mod))^2 ) / sum( (y-mean(y))^2 ) ) The first calculation seems OK, it gives the logicala values in models (from 0 to 1), but the second gives the negative values; higher corelation between the y and prediction gives more neagtive R2 value (up to -85). And my second question, looks logical but I need more teoretical answer; why R^2 (r-square) values are not appropriate for use with non-linear regression models (like exponential)? Thank you for your answers. Greetings, Kate -- View this message in context: http://r.789695.n4.nabble.com/compute-coefficient-of-determination-R-squared-for-GLM-maximum-likelihood-tp2261975p3495108.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ 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.
