trimcibt: Bootstrap-t method for one-sample test

In WRS2: A Collection of Robust Statistical Methods

Bootstrap-t method for one-sample test

Description

Compute a 1-alpha confidence interval for the trimmed mean using a bootstrap percentile t method.

Usage

trimcibt(x, nv = 0, tr = 0.2, alpha = 0.05, nboot = 200, ...)

Arguments

x	a numeric vector.
nv	value under H0.
tr	trim level for the mean.
alpha	alpha level.
nboot	number of bootstrap samples.
...	currently ignored.

Value

Returns an object of class "trimcibt" containing:

ci	95% confidence interval
estimate	trimmed mean
p.value	p-value
test.stat	t-statistic
tr	trimming level
n	number of effective observations

References

Wilcox, R. (2017). Introduction to Robust Estimation and Hypothesis Testing (4th ed.). Elsevier.

See Also

onesampb

Examples

  set.seed(123)
  x <- rnorm(30)
  trimcibt(x, nboot = 100)    ## H0: Psi = 0

WRS2 documentation built on March 19, 2024, 3:08 a.m.