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