test.WA: The Watson goodness-of-fit test for the gamma family

In gofgamma: Goodness-of-Fit Tests for the Gamma Distribution

Description

This function computes the goodness-of-fit test for the gamma family in the spirit of Watson. Note that this tests the composite hypothesis of fit to the family of gamma distributions, i.e. a bootstrap procedure is implemented to perform the test.

Usage

test.WA(data, boot = 500, alpha = 0.05)

Arguments

data	a vector of positive numbers.
boot	number of bootstrap iterations used to obtain critical value.
alpha	level of significance of the test.

Details

The Watson test is computed as described in Henze et. al. (2012). Critical values are obtained by a parametric bootstrap procedure, see crit.values.

Value

a list containing the value of the test statistic, the approximated critical value and a test decision on the significance level alpha:

$T.value

the value of the test statistic.

$cv

the approximated critical value.

$par.est

number of points used in approximation.

$Decision

the comparison of the critical value and the value of the test statistic.

$sig.level

level of significance chosen.

$boot.run

number of bootstrap iterations.

References

Henze, N., Meintanis, S.G., Ebner, B. (2012) "Goodness-of-fit tests for the Gamma distribution based on the empirical Laplace transform". Communications in Statistics - Theory and Methods, 41(9): 1543-1556. DOI

Examples

test.WA(stats::rgamma(20,3,6),boot=100)

gofgamma documentation built on April 29, 2020, 5:07 p.m.