test.HME1: The first Henze-Meintanis-Ebner goodness-of-fit test for the...

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

Description

This function computes the first goodness-of-fit test for the gamma family due to Henze, Meintanis and Ebner (2012).

Usage

test.HME1(data, a = 1, boot = 500, alpha = 0.05)

Arguments

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

Details

The test is of weighted L^2 type and uses a characterization of the distribution function of the gamma distribution. 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.HME1(stats::rgamma(20,3,6),boot=100)

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