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dc.contributor.authorSteele, Michael
dc.contributor.authorChaseling, Janet
dc.date.accessioned2017-05-03T11:02:26Z
dc.date.available2017-05-03T11:02:26Z
dc.date.issued2006
dc.date.modified2014-06-30T05:05:07Z
dc.identifier.issn0361-0918
dc.identifier.doi10.1080/03610910600880666
dc.identifier.urihttp://hdl.handle.net/10072/13798
dc.description.abstractThe comparative powers of six discrete goodness-of-fit test statistics for a uniform null distribution against a variety of fully specified alternative distributions are discussed. The results suggest that the test statistics based on the empirical distribution function for ordinal data (Kolmogorov-Smirnov, Cram鲭von Mises, and Anderson-Darling) are generally more powerful for trend alternative distributions. The test statistics for nominal (Pearson's chi-square and the nominal Kolmogorov-Smirnov) and circular data (Watson's test statistic) are shown to be generally more powerful for the investigated triangular (?), flat (or platykurtic type), sharp (or leptokurtic type), and bimodal alternative distributions.
dc.description.peerreviewedYes
dc.description.publicationstatusYes
dc.languageEnglish
dc.language.isoen_US
dc.publisherTaylor & Francis Group, LLC
dc.publisher.placeUK
dc.relation.ispartofstudentpublicationN
dc.relation.ispartofpagefrom1067
dc.relation.ispartofpageto1075
dc.relation.ispartofjournalCommunications in Statistics - Simulation and Computation
dc.relation.ispartofvolume35
dc.rights.retentionY
dc.subject.fieldofresearchMathematical Sciences
dc.subject.fieldofresearchInformation and Computing Sciences
dc.subject.fieldofresearchcode01
dc.subject.fieldofresearchcode08
dc.titlePowers of Discrete Goodness-of-Fit Test Statistics for a Uniform Null Against a Selection of Alternative Distributions
dc.typeJournal article
dc.type.descriptionC1 - Articles
dc.type.codeC - Journal Articles
gro.date.issued2006
gro.hasfulltextNo Full Text
gro.griffith.authorChaseling, Janet


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