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Skew Normal Boxplot and Outliers

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dc.contributor.author허명회-
dc.contributor.author이용구-
dc.date.accessioned2021-09-07T02:21:47Z-
dc.date.available2021-09-07T02:21:47Z-
dc.date.created2021-06-17-
dc.date.issued2012-
dc.identifier.issn2287-7843-
dc.identifier.urihttps://scholar.korea.ac.kr/handle/2021.sw.korea/110133-
dc.description.abstractWe frequently use Tukey's boxplot to identify outliers in the batch of observations of the continuous variable. In doing so, we implicitly assume that the underlying distribution belongs to the family of normal distributions. Such a practice of data handling is often superficial and improper, since in reality too many variables manifest the skewness. In this short paper, we build a modified boxplot and set the outlier identification procedure by assuming that the observations are generated from the skew normal distribution (Azzalini, 1985), which is an extension of the normal distribution. Statistical performance of the proposed procedure is examined with simulated datasets.-
dc.languageEnglish-
dc.language.isoen-
dc.publisher한국통계학회-
dc.titleSkew Normal Boxplot and Outliers-
dc.title.alternativeSkew Normal Boxplot and Outliers-
dc.typeArticle-
dc.contributor.affiliatedAuthor허명회-
dc.identifier.bibliographicCitationCommunications for Statistical Applications and Methods, v.19, no.4, pp.591 - 595-
dc.relation.isPartOfCommunications for Statistical Applications and Methods-
dc.citation.titleCommunications for Statistical Applications and Methods-
dc.citation.volume19-
dc.citation.number4-
dc.citation.startPage591-
dc.citation.endPage595-
dc.type.rimsART-
dc.identifier.kciidART001683762-
dc.description.journalClass2-
dc.description.journalRegisteredClasskci-
dc.subject.keywordAuthorBoxplot-
dc.subject.keywordAuthoroutlier-
dc.subject.keywordAuthorskew normal distribution.-
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