An overview of goodness-of-fit tests for the Poisson distribution

dc.contributor.authorMijburgh, P.A.
dc.contributor.authorVisagie, I.J.H. (Jaco)
dc.date.accessioned2020-10-03T11:38:15Z
dc.date.available2020-10-03T11:38:15Z
dc.date.issued2020
dc.description.abstractThe Poisson distribution has a large number of applications and is often used as a model in both a practical and a theoretical setting. As a result, various goodness-of-fit tests have been developed for this distribution. In this paper, we compare the finite sample power performance of ten of these tests against a wide range of alternative distributions for various sample sizes. The alternatives considered include, seemingly for the first time, weighted Poisson distributions. A number of additional tests are of historical importance although their power performance is not competitive against the remaining tests. These tests are discussed, but their powers are not included in the numerical analysis. The Monte Carlo study presented below indicates that the test with the best overall power performance is the test of Meintanis and Nikitin (2008), followed closely by the test of Rayner and Best (1990) (originally studied in Fisher, 1950).en_ZA
dc.description.departmentStatisticsen_ZA
dc.description.librarianhj2020en_ZA
dc.description.urihttps://sastat.org.za/journalen_ZA
dc.description.urihttp://www.journals.co.za/content/journal/sasjen_ZA
dc.identifier.citationMijburgh, P.A. & Visagie, I.J.H. 2020, 'An overview of goodness-of-fit tests for the Poisson distribution', South African Statistical Journal, vol. 54, no. 2, pp. 207-230.en_ZA
dc.identifier.issn0038-271X
dc.identifier.other10.37920/sasj.2020.54.2.6
dc.identifier.urihttp://hdl.handle.net/2263/76338
dc.language.isoenen_ZA
dc.publisherSouth African Statistical Associationen_ZA
dc.rights© 2020 South African Statistical Associationen_ZA
dc.subjectGoodness-of-fit testingen_ZA
dc.subjectPoisson distributionen_ZA
dc.subjectWarp-speed bootstrapen_ZA
dc.titleAn overview of goodness-of-fit tests for the Poisson distributionen_ZA
dc.typeArticleen_ZA

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