geary.norm.test: Geary test for normality
In normtest: Tests for Normality

Description Usage Arguments Details Value Author(s) References Examples

Performs Geary test for the composite hypothesis of normality, see Geary (1935).

1	geary.norm.test(x, nrepl=2000)

`x`	a numeric vector of data values.

nrepl

the number of replications in Monte Carlo simulation.

The Geary test for normality is based on the following statistic:

d = \frac{1}{ns}∑_{i=1}^n|X_i-\overline{X}|,

where

s^2=\frac{1}{n}∑_{i=1}^n(X_i-\overline{X})^2.

The p-value is computed by Monte Carlo simulation.

A list with class "htest" containing the following components:

`statistic`	the value of the Geary statistic.
`p.value`	the p-value for the test.
`method`	the character string "Geary test for normality".
`data.name`	a character string giving the name(s) of the data.

Ilya Gavrilov and Ruslan Pusev

Geary, R. C. (1935): The ratio of the mean deviation to the standard deviation as a test of normality. — Biometrika, vol. 27, pp. 310–332.

1 2	geary.norm.test(rnorm(100)) geary.norm.test(runif(100,-1,1))

	Geary test for normality

data:  rnorm(100)
d = 0.79226, p-value = 0.645


	Geary test for normality

data:  runif(100, -1, 1)
d = 0.89679, p-value < 2.2e-16