rpart (version 4.1-13)

residuals.rpart: Residuals From a Fitted Rpart Object

Description

Method for residuals for an rpart object.

Usage

# S3 method for rpart
residuals(object, type = c("usual", "pearson", "deviance"), ...)

Arguments

object

fitted model object of class "rpart".

type

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.

Value

Vector of residuals of type type from a fitted rpart object.

References

McCullagh P. and Nelder, J. A. (1989) Generalized Linear Models. London: Chapman and Hall.

Examples

# NOT RUN {
fit <- rpart(skips ~ Opening + Solder + Mask + PadType + Panel,
             data = solder, method = "anova")
summary(residuals(fit))
plot(predict(fit),residuals(fit))
# }