a vector of positive numbers. NOTE: <code>data</code> has to be the rescaled data, i.e. devided by the estimated <code>scale</code> parameter!

data

value of the estimated <code>shape</code> parameter.

k_estimator

This function computes the goodness-of-fit test statistic for the gamma family in the spirit of Anderson and Darling. 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, see <code><a rd-options="" href="/link/crit.values?package=gofgamma&version=1.0" data-mini-rdoc="gofgamma::crit.values">crit.values</a></code>.

We implement various classical tests for the composite hypothesis of testing the fit to the family of gamma distributions as the Kolmogorov-Smirnov test, the Cramer-von Mises test, the Anderson Darling test and the Watson test. For each test a parametric bootstrap procedure is implemented, as considered in Henze, Meintanis & Ebner (2012) <doi:10.1080/03610926.2010.542851>. The recent procedures presented in Henze, Meintanis & Ebner (2012) <doi:10.1080/03610926.2010.542851> and Betsch & Ebner (2019) <doi:10.1007/s00184-019-00708-7> are implemented. Estimation of parameters of the gamma law are implemented using the method of Bhattacharya (2001) <doi:10.1080/00949650108812100>.

Bruno Ebner

gofgamma

Goodness-of-Fit Tests for the Gamma Distribution

Lucas Butsch

Steffen Betsch

AD function

This function computes the goodness-of-fit test statistic for the gamma family in the spirit of Anderson and Darling. 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, see <code><a rd-options='' href='crit.values'>crit.values</a></code>.

AD: statistic of the Anderson-Darling goodness-of-fit test for the gamma family

Description

Usage

Arguments

Value

Details

References

Examples