@article{Liebenberg_Allison_2023, title={A Review of Goodness-of-Fit Tests for the Rayleigh Distribution}, volume={52}, url={https://ajs.or.at/index.php/ajs/article/view/1322}, DOI={10.17713/ajs.v52i1.1322}, abstractNote={<p>The Rayleigh distribution has recently become popular as a model for a range of phenomena. As a result, a number of goodness-of-fit tests have been developed for this distribution. In this paper, we provide the first overview of goodness-of-fit tests for the Rayleigh distribution and compare these tests in a Monte-Carlo study to identify the tests that provide the highest powers against a wide range of alternatives. Our findings suggest that two recently developed tests as well as a test based on the Laplace transform and a test based on the Hellinger distance are the better performing tests.</p>}, number={1}, journal={Austrian Journal of Statistics}, author={Liebenberg, Shawn and Allison, James}, year={2023}, month={Mar.}, pages={1–22} }