moments (version 0.14.1)

anscombe.test: Anscombe-Glynn test of kurtosis

Description

Performs Anscombe-Glynn test of kurtosis for normal samples

Usage

anscombe.test(x, alternative = c("two.sided", "less", "greater"))

Arguments

x

a numeric vector of data values.

alternative

a character string specifying the alternative hypothesis, must be one of '"two.sided"' (default), '"greater"' or '"less"'. You can specify just the initial letter.

Value

A list with class htest containing the following components:

statistic

the list containing kurtosis estimator and its transformation.

p.value

the p-value for the test.

alternative

a character string describing the alternative hypothesis.

method

a character string indicating what type of test was performed.

data.name

name of the data argument.

Details

Under the hypothesis of normality, data should have kurtosis equal to 3. This test has such null hypothesis and is useful to detect a significant difference of kurtosis in normally distributed data.

References

Anscombe, F.J., Glynn, W.J. (1983) Distribution of kurtosis statistic for normal statistics. Biometrika, 70, 1, 227-234

See Also

kurtosis

Examples

# NOT RUN {
set.seed(1234)
x = rnorm(1000)
kurtosis(x)
anscombe.test(x)
# }