kimber.exp.test: Kimber-Michael test for exponentiality

In exptest: Tests for Exponentiality

Description

Performs Kimber-Michael test for the composite hypothesis of exponentiality, see e.g. Michael (1983), Kimber (1985).

Usage

kimber.exp.test(x, nrepl=2000)

Arguments

x	a numeric vector of data values.

nrepl

the number of replications in Monte Carlo simulation.

Details

The Kimber-Michael test for exponentiality is based on the following statistic:

D = \max_i{≤ft| r_i - s_i\right|},

where

s_i = \frac{2}{π} \, \arcsin{√{1-\exp(-X_{(i)}/\overline{X})}}, \qquad r_i = \frac{2}{π} \, \arcsin{√{(i - 0.5)/n}}.

The p-value is computed by Monte Carlo simulation.

Value

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

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

Author(s)

Alexey Novikov and Ruslan Pusev

References

Kimber, A.C. (1985): Tests for the exponential, Weibull and Gumbel distributions based on the stabilized probability plot. — Biometrika, vol. 72, pp. 661–663.

Michael, J.R. (1983): The stabilized probability plot. — Biometrika, vol. 70, pp. 11–17.

Examples

kimber.exp.test(rexp(100))
kimber.exp.test(rchisq(100,2))

exptest documentation built on May 1, 2019, 8:01 p.m.