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Article: Outlier diagnostics in several multivariate samples

TitleOutlier diagnostics in several multivariate samples
Authors
KeywordsConfirmatory analysis
Diagnostics
High breakdown point
Multiple outliers
S-estimation
Several multivariate samples
Issue Date1999
PublisherWiley-Blackwell Publishing Ltd. The Journal's web site is located at http://www.blackwellpublishing.com/journal.asp?ref=0039-0526&site=1
Citation
Journal Of The Royal Statistical Society Series D: The Statistician, 1999, v. 48 n. 1, p. 73-84 How to Cite?
AbstractA few diagnostics are proposed for the identification of single outliers in several multivariate samples. As in outlier detection in other models such as the linear and non-linear regression models, the proposed outlier diagnostics are found to be equivalent. The high breakdown point S-estimation robust method is used for detecting multiple outliers in several samples. The method can avoid the common masking problem in outlier detection but may tend to declare too many observations as extreme. The adding-back confirmatory analysis is used for remedying this swamping problem. Some published reference (cut-off) values are suggested for distinguishing between 'good' and outlying observations. The methods proposed are applied to real and simulated data sets. Satisfactory results are obtained.
Persistent Identifierhttp://hdl.handle.net/10722/83008
ISSN
2005 Impact Factor: 0.833
References

 

DC FieldValueLanguage
dc.contributor.authorFung, WKen_HK
dc.date.accessioned2010-09-06T08:35:53Z-
dc.date.available2010-09-06T08:35:53Z-
dc.date.issued1999en_HK
dc.identifier.citationJournal Of The Royal Statistical Society Series D: The Statistician, 1999, v. 48 n. 1, p. 73-84en_HK
dc.identifier.issn0039-0526en_HK
dc.identifier.urihttp://hdl.handle.net/10722/83008-
dc.description.abstractA few diagnostics are proposed for the identification of single outliers in several multivariate samples. As in outlier detection in other models such as the linear and non-linear regression models, the proposed outlier diagnostics are found to be equivalent. The high breakdown point S-estimation robust method is used for detecting multiple outliers in several samples. The method can avoid the common masking problem in outlier detection but may tend to declare too many observations as extreme. The adding-back confirmatory analysis is used for remedying this swamping problem. Some published reference (cut-off) values are suggested for distinguishing between 'good' and outlying observations. The methods proposed are applied to real and simulated data sets. Satisfactory results are obtained.en_HK
dc.languageengen_HK
dc.publisherWiley-Blackwell Publishing Ltd. The Journal's web site is located at http://www.blackwellpublishing.com/journal.asp?ref=0039-0526&site=1en_HK
dc.relation.ispartofJournal of the Royal Statistical Society Series D: The Statisticianen_HK
dc.subjectConfirmatory analysisen_HK
dc.subjectDiagnosticsen_HK
dc.subjectHigh breakdown pointen_HK
dc.subjectMultiple outliersen_HK
dc.subjectS-estimationen_HK
dc.subjectSeveral multivariate samplesen_HK
dc.titleOutlier diagnostics in several multivariate samplesen_HK
dc.typeArticleen_HK
dc.identifier.emailFung, WK: wingfung@hku.hken_HK
dc.identifier.authorityFung, WK=rp00696en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.scopuseid_2-s2.0-0040883186en_HK
dc.identifier.hkuros43441en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-0040883186&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume48en_HK
dc.identifier.issue1en_HK
dc.identifier.spage73en_HK
dc.identifier.epage84en_HK
dc.publisher.placeUnited Kingdomen_HK
dc.identifier.scopusauthoridFung, WK=13310399400en_HK

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