A Novel Goodness-of-Fit Test for Cauchy Distribution

A. Pekgör and Jiancheng Jiang

Journal of Mathematics, 2023, vol. 2023, 1-14

Abstract: Recently, 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 Cramér–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.

Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jjmath:9200213

DOI: 10.1155/2023/9200213

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