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Article: Nonparametric confidence intervals based on extreme bootstrap percentiles

TitleNonparametric confidence intervals based on extreme bootstrap percentiles
Authors
KeywordsBootstrap
Confidence limit
Coverage
Edgeworth expansion
Equi-tailed
Extreme percentile
Monte Carlo
Noncoverage
Smooth function model
Issue Date2000
PublisherAcademia Sinica, Institute of Statistical Science. The Journal's web site is located at http://www.stat.sinica.edu.tw/statistica/
Citation
Statistica Sinica, 2000, v. 10 n. 2, p. 475-496 How to Cite?
AbstractMonte Carlo approximation of standard bootstrap confidence intervals relies on the drawing of a large number, B say, of bootstrap resamples. Conventional choice of B is often made on the order of 1,000. While this choice may prove to be more than sufficient for some cases, it may be far from adequate for others. A new approach is suggested to construct confidence intervals based on extreme bootstrap percentiles and an adaptive choice of B. It economizes on the computational effort in a problem-specific fashion, yielding stable confidence intervals of satisfactory coverage accuracy.
Persistent Identifierhttp://hdl.handle.net/10722/45351
ISSN
2021 Impact Factor: 1.330
2020 SCImago Journal Rankings: 1.240
References

 

DC FieldValueLanguage
dc.contributor.authorLee, SMSen_HK
dc.date.accessioned2007-10-30T06:23:33Z-
dc.date.available2007-10-30T06:23:33Z-
dc.date.issued2000en_HK
dc.identifier.citationStatistica Sinica, 2000, v. 10 n. 2, p. 475-496en_HK
dc.identifier.issn1017-0405en_HK
dc.identifier.urihttp://hdl.handle.net/10722/45351-
dc.description.abstractMonte Carlo approximation of standard bootstrap confidence intervals relies on the drawing of a large number, B say, of bootstrap resamples. Conventional choice of B is often made on the order of 1,000. While this choice may prove to be more than sufficient for some cases, it may be far from adequate for others. A new approach is suggested to construct confidence intervals based on extreme bootstrap percentiles and an adaptive choice of B. It economizes on the computational effort in a problem-specific fashion, yielding stable confidence intervals of satisfactory coverage accuracy.en_HK
dc.format.extent319232 bytes-
dc.format.extent2357 bytes-
dc.format.mimetypeapplication/pdf-
dc.format.mimetypetext/plain-
dc.languageengen_HK
dc.publisherAcademia Sinica, Institute of Statistical Science. The Journal's web site is located at http://www.stat.sinica.edu.tw/statistica/en_HK
dc.relation.ispartofStatistica Sinicaen_HK
dc.subjectBootstrapen_HK
dc.subjectConfidence limiten_HK
dc.subjectCoverageen_HK
dc.subjectEdgeworth expansionen_HK
dc.subjectEqui-taileden_HK
dc.subjectExtreme percentileen_HK
dc.subjectMonte Carloen_HK
dc.subjectNoncoverageen_HK
dc.subjectSmooth function modelen_HK
dc.titleNonparametric confidence intervals based on extreme bootstrap percentilesen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=1017-0405&volume=10&issue=2&spage=475&epage=496&date=2000&atitle=Nonparametric+confidence+intervals+based+on+extreme+bootstrap+percentilesen_HK
dc.identifier.emailLee, SMS: smslee@hku.hken_HK
dc.identifier.authorityLee, SMS=rp00726en_HK
dc.description.naturepublished_or_final_versionen_HK
dc.identifier.scopuseid_2-s2.0-0034414849en_HK
dc.identifier.hkuros62101-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-0034414849&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume10en_HK
dc.identifier.issue2en_HK
dc.identifier.spage475en_HK
dc.identifier.epage496en_HK
dc.publisher.placeTaiwan, Republic of Chinaen_HK
dc.identifier.scopusauthoridLee, SMS=24280225500en_HK
dc.identifier.issnl1017-0405-

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