An objective comparison between various goodness-of-fit tests for exponentiality

Abstract

The exponential distribution is a popular model both in practice and in theoretical work. As a result, a multitude of tests based on varied characterisations have been developed for testing the hypothesis that observed data are realised from this distribution. Many of the recently developed tests contain a tuning parameter, usually appearing in a weight function. In this dissertation, we compare the powers of 20 tests for exponentiality, some containing a tuning parameter and some that do not. To ensure an objective comparison between each of the tests, we employ a data-dependent choice of the tuning parameter for those tests that contain these parameters. The numerical comparisons presented are conducted for various sample sizes and for a large number of alternative distributions. The results of the simulation study show that the test with the best overall performance is the Baringhaus and Henze test, followed closely by the test by Henze and Meintanis; both tests contain a tuning parameter. The score test by Cox and Oakes performs the best among those tests that do not include a tuning parameter.