This function computes the second goodness-of-fit test for the gamma family due to Henze, Meintanis and Ebner (2012).
test.HME2(data, a = 4, boot = 500, alpha = 0.05)a vector of positive numbers.
positive tuning parameter.
number of bootstrap iterations used to obtain critical value.
level of significance of the test.
a list containing the value of the test statistic, the approximated critical value and a test decision on the significance level alpha:
$T.valuethe value of the test statistic.
$cvthe approximated critical value.
$par.estnumber of points used in approximation.
$Decisionthe comparison of the critical value and the value of the test statistic.
$sig.levellevel of significance chosen.
$boot.runnumber of bootstrap iterations.
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.
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
# NOT RUN {
test.HME2(stats::rgamma(20,3,6),boot=100)
# }
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