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hal.structure.identifierInstitut de Mathématiques de Bordeaux [IMB]
dc.contributor.authorNIKULIN, Mikhail
hal.structure.identifierDepartement of Statistics, Vilnius University
dc.contributor.authorVILIJANDAS, Bagdonavicius
hal.structure.identifierDepartement of Statistics, Vilnius University
dc.contributor.authorJULIUS, Kruopis
dc.date.created2011
dc.date.issued2011
dc.identifier.isbn9 781 848 212 695
dc.description.abstractEnThe book addressed the testing of hypotheses in non-parametric models in the general case for complete data samples. Classical non-parametric tests (goodness-of-fit , homogenneity, randomness, independence) of complete data are considered and explained. Tests features include the chi-squared and modified chi-squared tests, rank and homogeneity tests, and most of the test results are proved, with real applicatiuons illustrated using examples. The incorrect use of many tests, and their applications using commonly deployed statistical software is highlighted and discuss.
dc.language.isoen
dc.publisherISTE-WILEY
dc.subject.enComplete data
dc.subject.enchi-squared test
dc.subject.engoodness-of-fit test
dc.subject.enempirical processes
dc.subject.enrank test
dc.subject.ennon-parametric test
dc.subject.enmaximum likelihood estimator
dc.title.enNon-parametric Tests for Complete Data
dc.typeOuvrage
dc.subject.halMathématiques [math]/Statistiques [math.ST]
dc.subject.halStatistiques [stat]/Théorie [stat.TH]
dc.subject.halStatistiques [stat]/Applications [stat.AP]
bordeaux.page308 pages
hal.identifierhal-00782912
hal.version1
hal.popularnon
hal.audienceNon spécifiée
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-00782912v1
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