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dc.contributor.authorLiebenberg, Shawn Carl
dc.contributor.authorAllison, James Samuel
dc.contributor.authorNgatchou-Wandji, Joseph
dc.date.accessioned2020-11-05T11:26:49Z
dc.date.available2020-11-05T11:26:49Z
dc.date.issued2020
dc.identifier.citationLiebenberg, S.C. et al. 2020. On a new goodness-of-fit test for the Rayleigh distribution based on a conditional expectation characterization. Communications in statistics: theory and methods, (In press). [https://doi.org/10.1080/03610926.2020.1836220]en_US
dc.identifier.issn0361-0926
dc.identifier.issn1532-415X (Online)
dc.identifier.urihttp://hdl.handle.net/10394/36273
dc.identifier.urihttps://www.tandfonline.com/doi/full/10.1080/03610926.2020.1836220
dc.identifier.urihttps://doi.org/10.1080/03610926.2020.1836220
dc.description.abstractWe propose and study new goodness-of-fit tests for the Rayleigh distribution based on a characterization involving a conditional expectation. The asymptotic properties of the tests are explored and the performance of the new tests are evaluated and compared to that of existing tests by means of a Monte Carlo study. It is found that the newly proposed tests perform satisfactory compared to the competitor testsen_US
dc.language.isoenen_US
dc.publisherTaylor & Francisen_US
dc.subjectCharacterizationen_US
dc.subjectGoodness-of-fiten_US
dc.subjectRayleigh distributionen_US
dc.titleOn a new goodness-of-fit test for the Rayleigh distribution based on a conditional expectation characterizationen_US
dc.typeArticleen_US
dc.contributor.researchID20396236 - Liebenberg, Shawn Carl
dc.contributor.researchID11985682 - Allison, James Samuel


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