Visualizing multidimensional data in multiple groups
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Huh, Myung-Hoe | - |
dc.date.accessioned | 2021-09-03T10:39:37Z | - |
dc.date.available | 2021-09-03T10:39:37Z | - |
dc.date.created | 2021-06-16 | - |
dc.date.issued | 2017-02 | - |
dc.identifier.issn | 1225-066X | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/84851 | - |
dc.description.abstract | A typical approach to visualizing k (>= 2)-group multidimensional data is to use Fisher's canonical discriminant analysis (CDA). CDA finds the best low-dimensional subspace that accommodates k group centroids in the Mahalanobis space. This paper proposes an alternative visualization procedure functioning in the Euclidean space, which finds the primary dimension with maximum discrimination of k group centroids and the secondary dimension with maximum dispersion of all observational units. This hybrid procedure is especially useful when the number of groups k is two. | - |
dc.language | Korean | - |
dc.language.iso | ko | - |
dc.publisher | KOREAN STATISTICAL SOC | - |
dc.title | Visualizing multidimensional data in multiple groups | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Huh, Myung-Hoe | - |
dc.identifier.doi | 10.5351/KJAS.2017.30.1.083 | - |
dc.identifier.wosid | 000424584100007 | - |
dc.identifier.bibliographicCitation | KOREAN JOURNAL OF APPLIED STATISTICS, v.30, no.1, pp.83 - 93 | - |
dc.relation.isPartOf | KOREAN JOURNAL OF APPLIED STATISTICS | - |
dc.citation.title | KOREAN JOURNAL OF APPLIED STATISTICS | - |
dc.citation.volume | 30 | - |
dc.citation.number | 1 | - |
dc.citation.startPage | 83 | - |
dc.citation.endPage | 93 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.identifier.kciid | ART002201758 | - |
dc.description.journalClass | 2 | - |
dc.description.journalRegisteredClass | kci | - |
dc.relation.journalResearchArea | Mathematics | - |
dc.relation.journalWebOfScienceCategory | Statistics & Probability | - |
dc.subject.keywordAuthor | canonical discriminant analysis | - |
dc.subject.keywordAuthor | principal component analysis | - |
dc.subject.keywordAuthor | biplot | - |
dc.subject.keywordAuthor | Mahalanobis distance | - |
dc.subject.keywordAuthor | scaled Euclidean distance | - |
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.