anscombe.test | R Documentation |
Performs Anscombe-Glynn test of kurtosis for normal samples
anscombe.test(x, alternative = c("two.sided", "less", "greater"))
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. |
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 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. |
Lukasz Komsta
Anscombe, F.J., Glynn, W.J. (1983) Distribution of kurtosis statistic for normal statistics. Biometrika, 70, 1, 227-234
kurtosis
set.seed(1234) x = rnorm(1000) kurtosis(x) anscombe.test(x)
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