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Article: Robustness diagnosis for bootstrap inference

TitleRobustness diagnosis for bootstrap inference
Authors
KeywordsData depth
Omnidirectional data perturbations
R-value plot
Issue Date2011
Citation
Journal Of Computational And Graphical Statistics, 2011, v. 20 n. 2, p. 448-460 How to Cite?
AbstractWe propose a new robustness diagnostic scheme for bootstrap inference procedures. The scheme is adaptive to the data actually observed, applies readily to bootstrap inference output of diverse format, and therefore provides robustness diagnostics practically more relevant than most conventional robustness measures. Specifically, it monitors the sensitivity of the bootstrap distribution of inference output to specially designed omnidirectional data perturbations, and quantifies findings by a standardized measure with the aid of repeated resampling. The resulting measure, displayed in the form of an R-value plot, permits direct comparisons across different bootstrap procedures and across inference output of different types. Numerical examples are presented using both simulated and real-life data to illustrate applications of the scheme to estimation and hypothesis testing problems. This article has supplementary material online. © 2011 American Statistical Association.
Persistent Identifierhttp://hdl.handle.net/10722/125398
ISSN
2015 Impact Factor: 1.755
2015 SCImago Journal Rankings: 2.321
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. Lok is partially supported by a grant from the Research Grants Council of the Hong Kong Special Administrative Region, China (Project HKU 7128/02P). Stephen M. S. Lee is supported by a grant from the Research Grants Council of the Hong Kong Special Administrative Region, China (Project HKU 7029/04P).

References
Grants

 

DC FieldValueLanguage
dc.contributor.authorLok, WSen_HK
dc.contributor.authorLee, SMSen_HK
dc.date.accessioned2010-10-31T11:29:09Z-
dc.date.available2010-10-31T11:29:09Z-
dc.date.issued2011en_HK
dc.identifier.citationJournal Of Computational And Graphical Statistics, 2011, v. 20 n. 2, p. 448-460en_HK
dc.identifier.issn1061-8600en_HK
dc.identifier.urihttp://hdl.handle.net/10722/125398-
dc.description.abstractWe propose a new robustness diagnostic scheme for bootstrap inference procedures. The scheme is adaptive to the data actually observed, applies readily to bootstrap inference output of diverse format, and therefore provides robustness diagnostics practically more relevant than most conventional robustness measures. Specifically, it monitors the sensitivity of the bootstrap distribution of inference output to specially designed omnidirectional data perturbations, and quantifies findings by a standardized measure with the aid of repeated resampling. The resulting measure, displayed in the form of an R-value plot, permits direct comparisons across different bootstrap procedures and across inference output of different types. Numerical examples are presented using both simulated and real-life data to illustrate applications of the scheme to estimation and hypothesis testing problems. This article has supplementary material online. © 2011 American Statistical Association.en_HK
dc.languageengen_HK
dc.relation.ispartofJournal of Computational and Graphical Statisticsen_HK
dc.subjectData depthen_HK
dc.subjectOmnidirectional data perturbationsen_HK
dc.subjectR-value ploten_HK
dc.titleRobustness diagnosis for bootstrap inferenceen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=1061-8600&volume=&spage=&epage=&date=2010&atitle=Robustness+diagnosis+for+bootstrap+inferenceen_HK
dc.identifier.emailLee, SMS: smslee@hku.hken_HK
dc.identifier.authorityLee, SMS=rp00726en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1198/jcgs.2010.08034en_HK
dc.identifier.scopuseid_2-s2.0-80051629030en_HK
dc.identifier.hkuros179211en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-80051629030&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume20en_HK
dc.identifier.issue2en_HK
dc.identifier.spage448en_HK
dc.identifier.epage460en_HK
dc.identifier.isiWOS:000291845000014-
dc.publisher.placeUnited Statesen_HK
dc.relation.projectA robustness diagnostic scheme for general statistical procedures-
dc.relation.projectA study of m out of n bootstrap procedures for general M-estimation-
dc.identifier.scopusauthoridLok, WS=47061737400en_HK
dc.identifier.scopusauthoridLee, SMS=24280225500en_HK

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