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Article: A multivariate normal plot to detect nonnormality
Title | A multivariate normal plot to detect nonnormality | ||||||
---|---|---|---|---|---|---|---|
Authors | |||||||
Keywords | High-dimensional data Multivariate normality Principal component Spherical distribution | ||||||
Issue Date | 2009 | ||||||
Publisher | American Statistical Association. | ||||||
Citation | Journal Of Computational And Graphical Statistics, 2009, v. 18 n. 1, p. 53-72 How to Cite? | ||||||
Abstract | Royston proposed a normal probability plot to detect nonnormality of univariate data. The normal probability plot was provided with normalized acceptance regions to enhance its interpretability. By using the theory of spherical distributions and the idea of principal component analysis, we propose an approach to extending Royston's normal plot to detecting nonmultivariate normality in analyzing high-dimensional data. The performance of the proposed multivariate normal plot is demonstrated by Monte Carlo studies and illustrated by two real datasets. © 2009 American Statistical Association. | ||||||
Persistent Identifier | http://hdl.handle.net/10722/129033 | ||||||
ISSN | 2023 Impact Factor: 1.4 2023 SCImago Journal Rankings: 1.530 | ||||||
ISI Accession Number ID |
Funding Information: This research was supported by a University of Hong Kong research grant and The University of New Haven 2006 and 2007 Summer Faculty Fellowships. | ||||||
References |
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Liang, J | en_HK |
dc.contributor.author | Ng, KW | en_HK |
dc.date.accessioned | 2010-12-21T06:40:29Z | - |
dc.date.available | 2010-12-21T06:40:29Z | - |
dc.date.issued | 2009 | en_HK |
dc.identifier.citation | Journal Of Computational And Graphical Statistics, 2009, v. 18 n. 1, p. 53-72 | en_HK |
dc.identifier.issn | 1061-8600 | en_HK |
dc.identifier.uri | http://hdl.handle.net/10722/129033 | - |
dc.description.abstract | Royston proposed a normal probability plot to detect nonnormality of univariate data. The normal probability plot was provided with normalized acceptance regions to enhance its interpretability. By using the theory of spherical distributions and the idea of principal component analysis, we propose an approach to extending Royston's normal plot to detecting nonmultivariate normality in analyzing high-dimensional data. The performance of the proposed multivariate normal plot is demonstrated by Monte Carlo studies and illustrated by two real datasets. © 2009 American Statistical Association. | en_HK |
dc.language | eng | - |
dc.publisher | American Statistical Association. | - |
dc.relation.ispartof | Journal of Computational and Graphical Statistics | en_HK |
dc.subject | High-dimensional data | en_HK |
dc.subject | Multivariate normality | en_HK |
dc.subject | Principal component | en_HK |
dc.subject | Spherical distribution | en_HK |
dc.title | A multivariate normal plot to detect nonnormality | en_HK |
dc.type | Article | en_HK |
dc.identifier.openurl | http://library.hku.hk:4550/resserv?sid=HKU:IR&issn=1061-8600&volume=18&issue=1&spage=52&epage=72&date=2009&atitle=A+multivariate+normal+plot+to+detect+nonnormality | - |
dc.identifier.email | Ng, KW: kaing@hkucc.hku.hk | en_HK |
dc.identifier.authority | Ng, KW=rp00765 | en_HK |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1198/jcgs.2009.0004 | en_HK |
dc.identifier.scopus | eid_2-s2.0-64849093535 | en_HK |
dc.identifier.hkuros | 170818 | - |
dc.relation.references | http://www.scopus.com/mlt/select.url?eid=2-s2.0-64849093535&selection=ref&src=s&origin=recordpage | en_HK |
dc.identifier.volume | 18 | en_HK |
dc.identifier.issue | 1 | en_HK |
dc.identifier.spage | 53 | en_HK |
dc.identifier.epage | 72 | en_HK |
dc.identifier.isi | WOS:000268506000004 | - |
dc.publisher.place | United States | en_HK |
dc.identifier.scopusauthorid | Liang, J=7404541870 | en_HK |
dc.identifier.scopusauthorid | Ng, KW=7403178774 | en_HK |
dc.identifier.issnl | 1061-8600 | - |