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

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

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

Example output

Loading required package: orthopolynom
Loading required package: polynom

	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.