Statistical power of goodness-of-fit tests for type I left-censored data

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dc.contributor.authorFusek, Michalcs
dc.coverage.issue1cs
dc.coverage.volume52cs
dc.date.issued2023-03-07cs
dc.description.abstractType I doubly left-censored data often arise in environmental studies. In this paper, the power of the most frequently used goodness-of-fit tests (Kolmogorov-Smirnov, Cramér-von Mises, Anderson-Darling) is studied considering various sample sizes and degrees of censoring. Attention is paid to testing of the composite hypothesis that the data has a specific distribution with unknown parameters, which are estimated using the maximum likelihood method. Performance of the tests is assessed by means of Monte Carlo simulations for several distributions, specifically the Weibull, lognormal and gamma distributions, which are among the most frequently used distributions for modelling of environmental data. Finally, the tests are used for identification of the distribution of musk concentrations if fish tissue.en
dc.formattextcs
dc.format.extent51-61cs
dc.format.mimetypeapplication/pdfcs
dc.identifier.citationAustrian Journal of Statistics. 2023, vol. 52, issue 1, p. 51-61.en
dc.identifier.doi10.17713/ajs.v52i1.1348cs
dc.identifier.issn1026-597Xcs
dc.identifier.orcid0000-0002-9842-8384cs
dc.identifier.other175089cs
dc.identifier.researcheridE-4920-2018cs
dc.identifier.scopus39161155400cs
dc.identifier.urihttp://hdl.handle.net/11012/213632
dc.language.isoencs
dc.publisherAustrian Statistical Societycs
dc.relation.ispartofAustrian Journal of Statisticscs
dc.relation.urihttps://www.ajs.or.at/index.php/ajs/article/view/1348cs
dc.rightsCreative Commons Attribution 4.0 Internationalcs
dc.rights.accessopenAccesscs
dc.rights.sherpahttp://www.sherpa.ac.uk/romeo/issn/1026-597X/cs
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/cs
dc.subjectcensored dataen
dc.subjectgoodness-of-fit testen
dc.subjectempirical poweren
dc.subjecttype I left-censoringen
dc.titleStatistical power of goodness-of-fit tests for type I left-censored dataen
dc.type.driverarticleen
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
sync.item.dbidVAV-175089en
sync.item.dbtypeVAVen
sync.item.insts2025.02.03 15:40:49en
sync.item.modts2025.01.17 18:39:27en
thesis.grantorVysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií. Ústav matematikycs
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