I have understood that one commonly adds log(exposure) as an offset in the formula for GLMs, when dealing with poisson distributed rate data. I am dealing with insurance claim data where I want to predict the frequency i.e. #Claims/Exposure using a regression tree in R. My question is whether it is reasonable to add an log(exposure) offset here aswell? See code below for an example of what I would like to do.
CODE
tree <- rpart ( claims ~ age + ac + power + gas + brand + area + dens + ct
+ offset ( log ( expo )) ,
data = dat , method =" poisson ", parms = list ( shrink =1) ,
control = rpart . control ( xval =10 , minbucket =10000 , cp =0.001))