wrap.bm: Simulate a normal sample and compute a bootstrap distribution

In mdedge/stfspack: Functions to Support Statistical Thinking from Scratch

Description

Wraps boot.dist.1d, generating a normal sample and computing a bootstrap distribution for a statistic of interest. Plots a histogram of the bootstrap distribution and returns a list containing the mean and standard deviation of the bootstrap distribution.

Usage

wrap.bm(n, B, mu = 0, sigma = 1, FUN = mean, ...)

Arguments

n	The size of the normal sample to draw.
B	The number of bootstrap samples to draw from the normal sample.
mu	The expectation of the normal distribution from which the data are drawn.
sigma	The standard deviation of the normal distribution from which the data are drawn.
FUN	A function that computes the statistic of interest. FUN must have a vector of data as its first argument and must return a numeric vector of length 1 (i.e. a scalar).
...	Additional arguments passed to FUN.

Value

A list containing the mean and standard deviation of the bootstrap distribution.

Examples

wrap.bm(50, 1000, FUN = median)

mdedge/stfspack documentation built on May 9, 2019, 8:17 a.m.