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

## Description

Performs Hegazy-Green test for the hypothesis of uniformity.

## Usage

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

## Arguments

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

## Details

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

T_p = \frac{1}{n}âˆ‘_{i=1}^{n}{â‰¤ft|X_{(i)}-\frac{i}{n+1}\right|^p}.

The p-value is computed by Monte Carlo simulation.

## Value

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.

## Author(s)

Maxim Melnik and Ruslan Pusev

## References

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

## Examples

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

### Example output

Loading required package: orthopolynom

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


uniftest documentation built on May 1, 2019, 7:33 p.m.