[R] compute coefficient of determination (R-squared) for GLM (maximum likelihood)

[KateR]

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.