# kuiper.unif.test: Kuiper test for uniformity In uniftest: Tests for Uniformity

## Description

Performs Kuiper test for the hypothesis of uniformity, see Kuiper (1960).

## Usage

 1 kuiper.unif.test(x, nrepl=2000) 

## Arguments

 x a numeric vector of data values.
 nrepl the number of replications in Monte Carlo simulation.

## Details

The Kuiper test for uniformity is based on the following statistic:

V = \max_i≤ft(\frac{i}{n}-X_{(i)}\right) + \max_i≤ft(X_{(i)}-\frac{i-1}{n}\right)

The p-value is computed by Monte Carlo simulation.

## Value

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

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

## Author(s)

Maxim Melnik and Ruslan Pusev

## References

Kuiper, N.H. (1960): Tests concerning random points on a circle. — Proc. Kon. Ned. Akad. Wetensch., Ser. A, vol. 63, pp. 38–47.

## Examples

 1 2 kuiper.unif.test(runif(100,0,1)) kuiper.unif.test(rbeta(100,0.5,0.5)) 

### Example output

Loading required package: orthopolynom

Kuiper test for uniformity

data:  runif(100, 0, 1)
V = 1.8258, p-value = 0.277

Kuiper test for uniformity

data:  rbeta(100, 0.5, 0.5)
V = 1.9246, p-value = 0.019


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