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Article: A new statistical depth function with applications to multimodal data

TitleA new statistical depth function with applications to multimodal data
Authors
KeywordsCentre-outward ordering
Data depth
Interpoint distance
Multimodality
Issue Date2011
PublisherTaylor & Francis Ltd. The Journal's web site is located at http://www.tandf.co.uk/journals/titles/10485252.asp
Citation
Journal Of Nonparametric Statistics, 2011, v. 23 n. 3, p. 617-631 How to Cite?
AbstractWe propose a new statistical depth function based on interpoint distances, which has the distinct property of respecting multimodality in data configurations. This property proves to be especially relevant to many inference problems including confidence region construction, classification, tests for equality of populations, p-value computation, etc. With specification of an appropriate interpoint distance, our depth function also applies to infinite-dimensional data. A number of examples are used to illustrate the diverse applicability of our proposed depth function in different problem settings, where the conventional centre-outward ordering depth functions are found to be inadequate. © American Statistical Association and Taylor & Francis 2011.
Persistent Identifierhttp://hdl.handle.net/10722/139708
ISSN
2015 Impact Factor: 0.446
2015 SCImago Journal Rankings: 0.980
ISI Accession Number ID
Funding AgencyGrant Number
Research Grants Council of the Hong Kong Special Administrative Region, ChinaHKU 7128/02P
HKU 7029/04P
Funding Information:

W.S.L. was partially supported by a grant from the Research Grants Council of the Hong Kong Special Administrative Region, China (Project No. HKU 7128/02P). S.M.S.L. was supported by a grant from the Research Grants Council of the Hong Kong Special Administrative Region, China (Project No. HKU 7029/04P).

References
Grants

 

DC FieldValueLanguage
dc.contributor.authorLok, WSen_HK
dc.contributor.authorLee, SMSen_HK
dc.date.accessioned2011-09-23T05:54:43Z-
dc.date.available2011-09-23T05:54:43Z-
dc.date.issued2011en_HK
dc.identifier.citationJournal Of Nonparametric Statistics, 2011, v. 23 n. 3, p. 617-631en_HK
dc.identifier.issn1048-5252en_HK
dc.identifier.urihttp://hdl.handle.net/10722/139708-
dc.description.abstractWe propose a new statistical depth function based on interpoint distances, which has the distinct property of respecting multimodality in data configurations. This property proves to be especially relevant to many inference problems including confidence region construction, classification, tests for equality of populations, p-value computation, etc. With specification of an appropriate interpoint distance, our depth function also applies to infinite-dimensional data. A number of examples are used to illustrate the diverse applicability of our proposed depth function in different problem settings, where the conventional centre-outward ordering depth functions are found to be inadequate. © American Statistical Association and Taylor & Francis 2011.en_HK
dc.languageengen_US
dc.publisherTaylor & Francis Ltd. The Journal's web site is located at http://www.tandf.co.uk/journals/titles/10485252.aspen_HK
dc.relation.ispartofJournal of Nonparametric Statisticsen_HK
dc.subjectCentre-outward orderingen_HK
dc.subjectData depthen_HK
dc.subjectInterpoint distanceen_HK
dc.subjectMultimodalityen_HK
dc.titleA new statistical depth function with applications to multimodal dataen_HK
dc.typeArticleen_HK
dc.identifier.emailLee, SMS: smslee@hku.hken_HK
dc.identifier.authorityLee, SMS=rp00726en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1080/10485252.2011.553953en_HK
dc.identifier.scopuseid_2-s2.0-80052283364en_HK
dc.identifier.hkuros195591en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-80052283364&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume23en_HK
dc.identifier.issue3en_HK
dc.identifier.spage617en_HK
dc.identifier.epage631en_HK
dc.identifier.isiWOS:000299693300003-
dc.publisher.placeUnited Kingdomen_HK
dc.relation.projectA study of m out of n bootstrap procedures for general M-estimation-
dc.relation.projectA robustness diagnostic scheme for general statistical procedures-
dc.identifier.scopusauthoridLok, WS=47061737400en_HK
dc.identifier.scopusauthoridLee, SMS=24280225500en_HK

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