xpred.arbor
Return Cross-Validated Predictions

### Description

Gives the predicted values for an arbor fit, under cross validation, for a set of complexity parameter values.

### Usage

    xpred.arbor(fit, xval = 10, cp)

### Arguments

fit | an arbor object.
xval | integer number of cross-validation groups. This may also be an explicit list of integers that define the cross-validation group for each observation.
cp | vector of arbitrary length giving the desired set of complexity parameter values. By default it is taken from the cptable component of the fit.

### Details

Complexity penalties are actually ranges, not values. If the cp values found in the table were .36, .28, and .13, for instance, this means that the first row of the table holds for all complexity penalties in the range [.36,1], the second row for cp in the range [.28, .36) and the third row for [.13,.28). By default, the geometric mean of each interval is used for cross validation.
Value
A matrix with one row for each observation and one column for each complexity value is returned.
See Also
arbor
Examples

    library("arbor")
    data(car.test.frame, package = "Sdatasets")
    fit <- arbor(Mileage ~ Weight, car.test.frame)
    xmat <- xpred.arbor(fit)
    xerr <- (xmat - car.test.frame$Mileage)^2
    apply(xerr, 2, sum)  # cross-validated error estimate
    # Approx same result as rel. error from printcp(fit)
    apply(xerr, 2, sum)/var(car.test.frame$Mileage)

Package arbor version 6.1.5-18
Package Index