Method for residuals for an rpart object.
# S3 method for rpart
residuals(object, type = c("usual", "pearson", "deviance"), ...)Vector of residuals of type type from a fitted rpart object.
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.
McCullagh P. and Nelder, J. A. (1989) Generalized Linear Models. London: Chapman and Hall.
fit <- rpart(skips ~ Opening + Solder + Mask + PadType + Panel,
data = solder.balance, method = "anova")
summary(residuals(fit))
plot(predict(fit),residuals(fit))
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