Anscombe-Glynn test of kurtosis
Performs Anscombe-Glynn test of kurtosis for normal samples
anscombe.test(x, alternative = c("two.sided", "less", "greater"))
- a numeric vector of data values.
- a character string specifying the alternative hypothesis, must be one of '"two.sided"' (default), '"greater"' or '"less"'. You can specify just the initial letter.
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.
- A list with class
- the list containing kurtosis estimator and its transformation.
- the p-value for the test.
- a character string describing the alternative hypothesis.
- a character string indicating what type of test was performed.
- name of the data argument.
htestcontaining the following components:
Anscombe, F.J., Glynn, W.J. (1983) Distribution of kurtosis statistic for normal statistics. Biometrika, 70, 1, 227-234
set.seed(1234) x = rnorm(1000) kurtosis(x) anscombe.test(x)