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A Note on the Nonparametric Tests for the Grouped Data

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dc.contributor.author홍승만-
dc.contributor.author박효일-
dc.date.accessioned2021-09-05T13:10:40Z-
dc.date.available2021-09-05T13:10:40Z-
dc.date.created2021-06-17-
dc.date.issued2014-
dc.identifier.issn1229-2354-
dc.identifier.urihttps://scholar.korea.ac.kr/handle/2021.sw.korea/99850-
dc.description.abstractIn this research, we consider to compare efficiency among tests used for the grouped data through a simulation study. We consider two kinds of the chi-square tests used for the categorical data and the nonparametric linear rank test used for the grouped data. For this, first of all, we formulize the grouped data by introducing several notation and review the test statistics with their corresponding asymptotic distributions. Then we obtain the empirical powers to compare efficiency under the location translation model by varying the value of location translation parameter with five different distributions and three sets of sample sizes through a simulation study. Finally, we discuss some interesting features for the nonparametric test procedures for the grouped data and comments briefly on the grouped data as concluding remarks.-
dc.languageEnglish-
dc.language.isoen-
dc.publisher한국자료분석학회-
dc.titleA Note on the Nonparametric Tests for the Grouped Data-
dc.title.alternativeA Note on the Nonparametric Tests for the Grouped Data-
dc.typeArticle-
dc.contributor.affiliatedAuthor홍승만-
dc.identifier.bibliographicCitationJournal of The Korean Data Analysis Society, v.16, no.6, pp.2901 - 2906-
dc.relation.isPartOfJournal of The Korean Data Analysis Society-
dc.citation.titleJournal of The Korean Data Analysis Society-
dc.citation.volume16-
dc.citation.number6-
dc.citation.startPage2901-
dc.citation.endPage2906-
dc.type.rimsART-
dc.identifier.kciidART001941251-
dc.description.journalClass2-
dc.description.journalRegisteredClasskci-
dc.subject.keywordAuthorchi-square test-
dc.subject.keywordAuthorgrouped data-
dc.subject.keywordAuthorlinear rank test-
dc.subject.keywordAuthorlocation translation model-
dc.subject.keywordAuthornonparametric test-
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