frosini.unif.test: Frosini test for uniformity

In uniftest: Tests for Uniformity

Description

Performs Frosini test for the hypothesis of uniformity, see Frosini (1987).

Usage

frosini.unif.test(x, nrepl=2000)

Arguments

x	a numeric vector of data values.

nrepl

the number of replications in Monte Carlo simulation.

Details

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

B_n = \frac{1}{√{n}}∑_{i=1}^n{≤ft| X_{(i)} - \frac{i-0.5}{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 Frosini statistic.
p.value	the p-value for the test.
method	the character string "Frosini test for uniformity".
data.name	a character string giving the name(s) of the data.

Author(s)

Maxim Melnik and Ruslan Pusev

References

Frosini, B.V. (1987): On the distribution and power of a goodness-of-fit statistic with parametric and nonparametric applications, "Goodness-of-fit". (Ed. by Revesz P., Sarkadi K., Sen P.K.) — Amsterdam-Oxford-New York: North-Holland. — Pp. 133–154.

Examples

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

Example output

Loading required package: orthopolynom
Loading required package: polynom

	Frosini test for uniformity

data:  runif(100, 0, 1)
B = 0.21003, p-value = 0.762


	Frosini test for uniformity

data:  runif(100, 0.1, 0.9)
B = 0.80286, p-value = 0.0025

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