Kochar test for exponentiality

Description

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

Usage

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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

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