Pekgor, A.2024-02-232024-02-2320232314-46292314-4785https://doi.org/10.1155/2023/9200213https://hdl.handle.net/20.500.12452/14260Recently, several goodness-of-fit tests for Cauchy distribution have been introduced based on Kullback-Leibler divergence and likelihood ratio. It is claimed that these tests are more powerful than the well-known goodness-of-fit tests such as Kolmogorov-Smirnov, Anderson-Darling, and Cramer-von Mises under some cases. In this study, a novel goodness-of-fit test is proposed for the Cauchy distribution and the asymptotic null distribution of the test statistic is derived. The critical values of the proposed test are also determined through a Monte Carlo simulation for different sample sizes. The power analysis shows that the proposed test is more powerful than the current tests under certain cases.eninfo:eu-repo/semantics/openAccess[Keyword Not Available]Article20232-s2.0-85151532687Q3WOS:00095656250000310.1155/2023/9200213