kochar.exp.test: Kochar test for exponentiality

In exptest: Tests for Exponentiality

Description

Performs Kochar test for the composite hypothesis of exponentiality, see e.g. Kochar (1985).

Usage

kochar.exp.test(x, simulate.p.value=FALSE, nrepl=2000)

Arguments

x	a numeric vector of data values.

simulate.p.value	a logical value indicating whether to compute p-values by Monte Carlo simulation.
nrepl	the number of replications in Monte Carlo simulation.

Details

The Kochar test for exponentiality is based on the following statistic:

T = √{\frac{108n}{17}}\frac{∑_{i=1}^n{J(i/(n+1))X_{(i)}}}{∑_{i=1}^n{X_i}},

where

J(u) = 2(1-u)[1-\log{(1-u)}] - 1.

The statistic T is asymptotically standard normal.

Value

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

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

Author(s)

Alexey Novikov and Ruslan Pusev

References

Kochar, S.C. (1985): Testing exponenttality against monotone failure rate average. — Communications in Statistics – Theory and Methods, vol. 14, pp. 381–392.

Examples

kochar.exp.test(rexp(100))
kochar.exp.test(rchisq(100,1))

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