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
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)