hegazy.unif.test: Hegazy-Green test for uniformity
In uniftest: Tests for Uniformity

Description Usage Arguments Details Value Author(s) References Examples

Performs Hegazy-Green test for the hypothesis of uniformity.

1	hegazy.unif.test(x, nrepl=2000, p=1)

`x`	a numeric vector of data values.
`p`	a parameter of the test (see below).
`nrepl`	the number of replications in Monte Carlo simulation.

The Hegazy-Green test for uniformity is based on the following statistic:

T_p = \frac{1}{n}∑_{i=1}^{n}{≤ft|X_{(i)}-\frac{i}{n+1}\right|^p}.

The p-value is computed by Monte Carlo simulation.

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

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

Maxim Melnik and Ruslan Pusev

Hegazy, Y. A. S. and Green, J. R. (1975): Some new goodness-of-fit tests using order statistics. — Journal of the Royal Statistical Society. Series C (Applied Statistics), vol. 24, pp. 299–308.

1 2	hegazy.unif.test(runif(100,0,1)) hegazy.unif.test(runif(100,0.1,0.9))

Loading required package: orthopolynom
Loading required package: polynom

	Hegazy-Green test for uniformity

data:  runif(100, 0, 1)
T = 0.043473, p-value = 0.169


	Hegazy-Green test for uniformity

data:  runif(100, 0.1, 0.9)
T = 0.043784, p-value = 0.1655