fitted model object of class "rpart".

Indicates the type of residual desired.

For regression or anova trees all three residual definitions reduce to y - fitted. This is the residual returned for user method trees as well.

For classification trees the usual residuals are the misclassification losses L(actual, predicted) where L is the loss matrix. With default losses this residual is 0/1 for correct/incorrect classification. The pearson residual is (1-fitted)/sqrt(fitted(1-fitted)) and the deviance residual is sqrt(minus twice logarithm of fitted).

For poisson and exp (or survival) trees, the usual residual is the observed - expected number of events. The pearson and deviance residuals are as defined in McCullagh and Nelder.

further arguments passed to or from other methods.