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exptest (version 1.2)

cvm.exp.test: Cramer-von Mises test for exponentiality

Description

Performs Cramer-von Mises test for the composite hypothesis of exponentiality, see e.g. Henze and Meintanis (2005, Sec. 2.1).

Usage

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

Arguments

x
a numeric vector of data values.
nrepl
the number of replications in Monte Carlo simulation.

Value

  • A list with class "htest" containing the following components:
  • statisticthe value of the Cramer-von Mises statistic.
  • p.valuethe p-value for the test.
  • methodthe character string "Cramer-von Mises test for exponentiality".
  • data.namea character string giving the name(s) of the data.

Details

The Cramer-von Mises test for exponentiality is based on the following statistic: $$\omega^2_n =\int_0^\infty (F_n(x)-(1-\exp(-x)))^2\exp(-x)dx,$$ where $F_n$ is the empirical distribution function of the scaled data $Y_j=X_j/\overline{X}$. The p-value is computed by Monte Carlo simulation.

References

Henze, N. and Meintanis, S.G. (2005): Recent and classical tests for exponentiality: a partial review with comparisons. --- Metrika, vol. 61, pp. 29--45.

Examples

Run this code
cvm.exp.test(rexp(100))
cvm.exp.test(runif(100, min = 50, max = 100))

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