# Kochar test for exponentiality

### Description

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

### Usage

 1 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

 1 2 kochar.exp.test(rexp(100)) kochar.exp.test(rchisq(100,1)) 

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