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Conference Paper: A New Notion of Data Depth Based on Goodness-of-Fit Tests

TitleA New Notion of Data Depth Based on Goodness-of-Fit Tests
Authors
KeywordsData Depth
Goodness-of-Fit Tests
Multimodality
Issue Date2009
PublisherAmerican Statistical Association.
Citation
The 2009 Joint Statistical Meetings (JSM), Washington, DC., 1-6 August 2009. How to Cite?
AbstractData depth provides a natural means to rank multivariate vectors with respect to an underlying multivariate distribution. Most existing depth functions emphasize a center-outward ordering of data points, which may fail to capture other important distributional features such as multimodality of concern to certain statistical applications. Such inadequacy motivates us to develop a novel notion of data depth with emphasis on 'representativeness' rather than 'centrality.' Derived essentially from a choice of goodness-of-fit test statistic, the new notion calls for a new interpretation of 'depth' more akin to the concept of density instead of location. It copes well with multivariate data exhibiting multimodality in particular. The new definition also extends naturally to a depth measure for patterns of points as well as for singletons.
DescriptionTheme: Statistics: From Evidence to Policy
Abstract no. 303401
Persistent Identifierhttp://hdl.handle.net/10722/110172

 

DC FieldValueLanguage
dc.contributor.authorDong, Yen_HK
dc.contributor.authorLee, SMSen_HK
dc.date.accessioned2010-09-26T01:54:20Z-
dc.date.available2010-09-26T01:54:20Z-
dc.date.issued2009en_HK
dc.identifier.citationThe 2009 Joint Statistical Meetings (JSM), Washington, DC., 1-6 August 2009.-
dc.identifier.urihttp://hdl.handle.net/10722/110172-
dc.descriptionTheme: Statistics: From Evidence to Policy-
dc.descriptionAbstract no. 303401-
dc.description.abstractData depth provides a natural means to rank multivariate vectors with respect to an underlying multivariate distribution. Most existing depth functions emphasize a center-outward ordering of data points, which may fail to capture other important distributional features such as multimodality of concern to certain statistical applications. Such inadequacy motivates us to develop a novel notion of data depth with emphasis on 'representativeness' rather than 'centrality.' Derived essentially from a choice of goodness-of-fit test statistic, the new notion calls for a new interpretation of 'depth' more akin to the concept of density instead of location. It copes well with multivariate data exhibiting multimodality in particular. The new definition also extends naturally to a depth measure for patterns of points as well as for singletons.-
dc.languageengen_HK
dc.publisherAmerican Statistical Association.-
dc.relation.isformatofJoint Statistical Meetings (JSM)-
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.subjectData Depth-
dc.subjectGoodness-of-Fit Tests-
dc.subjectMultimodality-
dc.titleA New Notion of Data Depth Based on Goodness-of-Fit Testsen_HK
dc.typeConference_Paperen_HK
dc.identifier.emailLee, SMS: smslee@hku.hken_HK
dc.identifier.authorityLee, SMS=rp00726en_HK
dc.identifier.hkuros163468en_HK
dc.publisher.placeUnited States-
dc.customcontrol.immutableyiu 140929-
dc.customcontrol.immutablesml 151002-

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