New goodness-of-fit tests for the Kumaraswamy distribution

dc.contributor.authorGiles, David E.
dc.date.accessioned2024-05-17T22:33:15Z
dc.date.available2024-05-17T22:33:15Z
dc.date.issued2024
dc.description.abstractThe two-parameter distribution known as the Kumaraswamy distribution is a very flexible alternative to the beta distribution with the same (0,1) support. Originally proposed in the field of hydrology, it has subsequently received a good deal of positive attention in both the theoretical and applied statistics literatures. Interestingly, the problem of testing formally for the appropriateness of the Kumaraswamy distribution appears to have received little or no attention to date. To fill this gap, in this paper, we apply a “biased transformation” methodology to several standard goodness-of-fit tests based on the empirical distribution function. A simulation study reveals that these (modified) tests perform well in the context of the Kumaraswamy distribution, in terms of both their low size distortion and respectable power. In particular, the “biased transformation” Anderson–Darling test dominates the other tests that are considered.
dc.description.reviewstatusReviewed
dc.description.scholarlevelFaculty
dc.identifier.citationGiles, D. E. (2024). New goodness-of-fit tests for the Kumaraswamy distribution. Stats, 7(2), 373–389. https://doi.org/10.3390/stats7020023
dc.identifier.urihttps://doi.org/10.3390/stats7020023
dc.identifier.urihttps://hdl.handle.net/1828/16529
dc.language.isoen
dc.publisherStats
dc.rightsAttribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectgoodness-of-fit testing
dc.subjectempirical distribution function
dc.subjectKumaraswamy distribution
dc.subject.departmentDepartment of Economics
dc.titleNew goodness-of-fit tests for the Kumaraswamy distribution
dc.typeArticle

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