test.HME1 {gofgamma} | R Documentation |
The first Henze-Meintanis-Ebner goodness-of-fit test for the gamma family
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)