Skew Normal Boxplot and Outliers
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 허명회 | - |
dc.contributor.author | 이용구 | - |
dc.date.accessioned | 2021-09-07T02:21:47Z | - |
dc.date.available | 2021-09-07T02:21:47Z | - |
dc.date.created | 2021-06-17 | - |
dc.date.issued | 2012 | - |
dc.identifier.issn | 2287-7843 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/110133 | - |
dc.description.abstract | We 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.language | English | - |
dc.language.iso | en | - |
dc.publisher | 한국통계학회 | - |
dc.title | Skew Normal Boxplot and Outliers | - |
dc.title.alternative | Skew Normal Boxplot and Outliers | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | 허명회 | - |
dc.identifier.bibliographicCitation | Communications for Statistical Applications and Methods, v.19, no.4, pp.591 - 595 | - |
dc.relation.isPartOf | Communications for Statistical Applications and Methods | - |
dc.citation.title | Communications for Statistical Applications and Methods | - |
dc.citation.volume | 19 | - |
dc.citation.number | 4 | - |
dc.citation.startPage | 591 | - |
dc.citation.endPage | 595 | - |
dc.type.rims | ART | - |
dc.identifier.kciid | ART001683762 | - |
dc.description.journalClass | 2 | - |
dc.description.journalRegisteredClass | kci | - |
dc.subject.keywordAuthor | Boxplot | - |
dc.subject.keywordAuthor | outlier | - |
dc.subject.keywordAuthor | skew normal distribution. | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
(02841) 서울특별시 성북구 안암로 14502-3290-1114
COPYRIGHT © 2021 Korea University. All Rights Reserved.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.