trimcibt: Bootstrap-t method for one-sample test

Description Usage Arguments Value References See Also Examples

View source: R/trimcibt.R

Description

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

Usage

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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

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

WRS2 documentation built on July 20, 2021, 9:06 a.m.

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