bootControl: Control object for bootstrap samples

In perry: Resampling-Based Prediction Error Estimation for Regression Models

Description

Generate an object that controls how to draw bootstrap samples and which bootstrap estimator of prediction error to compute.

Usage

bootControl(R = 1, type = c("0.632", "out-of-bag"), grouping = NULL)

Arguments

R	an integer giving the number of bootstrap samples.
type	a character string specifying a bootstrap estimator. Possible values are "0.632" (the default), or "out-of-bag".
grouping	a factor specifying groups of observations.

Value

An object of class "bootControl" with the following components:

R

an integer giving the number of bootstrap samples.

type

a character string specifying the type of bootstrap estimator.

grouping

if supplied, a factor specifying groups of observations. The groups will then be resampled rather than individual observations such that all observations within a group belong either to the bootstrap sample or the test data.

Author(s)

Andreas Alfons

References

Efron, B. (1983) Estimating the error rate of a prediction rule: improvement on cross-validation. Journal of the American Statistical Association, 78(382), 316–331.

See Also

perrySplits, bootSamples, foldControl, splitControl

Examples

set.seed(1234)  # set seed for reproducibility
perrySplits(20, bootControl())
perrySplits(20, bootControl(R = 10))

perry documentation built on Nov. 3, 2021, 5:08 p.m.