residuals.rpart {rpart} | R Documentation

## Residuals From a Fitted Rpart Object

### Description

Method for `residuals` for an `rpart` object.

### Usage

    ## S3 method for class '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 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.

### 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

    data(solder)
    fit <- rpart(skips ~ Opening + Solder + Mask + PadType + Panel,
           data=solder, method='anova')
    summary(residuals(fit))
    plot(predict(fit),residuals(fit))

[Package Contents]