bootstrap: Bootstrap Estimation

Description

Samples randomly from the elements of object with replacement.

Usage

bootstrap(object, ...)
# S4 method for numeric
bootstrap(object, do, n, ..., f = NULL)

Value

If f is NULL (the default), bootstrap() returns a named numeric

vector with the following elements:

original: The observed value of do applied to object.
mean: The bootstrap estimate of mean of do.
bias: The bootstrap estimate of bias of do.
error: he bootstrap estimate of standard error of do.

If f is a function, bootstrap() returns the result of f applied to the n values of do.

Arguments

object: A numeric vector.
...: Extra arguments to be passed to do.
do: A function that takes object as an argument and returns a single numeric value.
n: A non-negative integer giving the number of bootstrap replications.
f: A function that takes a single numeric vector (the result of do) as argument.

Author

N. Frerebeau

Examples

Run this code

x <- rnorm(20)

## Bootstrap
bootstrap(x, do = mean, n = 100)

## Estimate the 25th and 95th percentiles
quant <- function(x) { quantile(x, probs = c(0.25, 0.75)) }
bootstrap(x, n = 100, do = mean, f = quant)

## Get the n bootstrap values
bootstrap(x, n = 100, do = mean, f = function(x) { x })

## Jackknife
jackknife(x, do = mean) # Sample mean

## Get the leave-one-out values instead of summary
jackknife(x, do = mean, f = function(x) { x })