Hello,
 
I'm fitting a Poisson GLM with the glm( ) function and I would like to know how 
to obtain the confidence intervals for predictions (fitted values)...
I mean like in function lm( ):
 
                prediction.matrix=exp(predict(model1.lm,interval="prediction")  
  
      
(where model1.lm is assumed to be a log-linear model fitted with the lm() 
function.)
 
Is there any function which can do it? If not how can I compute the prediction 
intervals from the fitted values? Is it the same for "quasipoisson" models?
 
Thanks you very much!
 
Annexe: for example I use:
model2.glm=glm(Y~X1+X2, family="poisson")
 
 
 
 
_________________________________________________________________
[[elided Hotmail spam]]

        [[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.

Reply via email to