File Download
  Links for fulltext
     (May Require Subscription)
  • Find via Find It@HKUL
Supplementary

Article: Asymptotic iterated bootstrap confidence intervals

TitleAsymptotic iterated bootstrap confidence intervals
Authors
KeywordsAsymptotic
Bootstrap
Coverage error
Edgeworth expansion
Iterated bootstrap
Issue Date1995
PublisherInstitute of Mathematical Statistics.
Citation
Annals of Statistics, 1995, v. 23 n. 4, p. 1301-1330 How to Cite?
AbstractAn iterated bootstrap confidence interval requires an additive correction to be made to the nominal coverage level of an uncorrected interval. Such correction is usually performed using a computationally intensive Monte Carlo simulation involving two nested levels of bootstrap sampling. Asymptotic expansions of the required correction and the iterated interval endpoints are used to provide two new computationally efficient methods for constructing an approximation to the iterated bootstrap confidence interval. The first asymptotic interval replaces the need for a second level of bootstrap sampling with a series of preliminary analytic calculations, which are readily automated, and from which an approximation to the coverage correction is easily obtained. The second interval directly approximates the endpoints of the iterated interval and yields, for the first time, the possibility of constructing an approximation to an iterated bootstrap confidence interval which does not require any resampling. The theoretical properties of the two intervals are considered. The computation required for their construction is detailed and has been coded in a fully automatic user-friendly Fortran program which may be obtained by anonymous ftp. A simulation study which illustrates their effectiveness on three examples is presented.
Persistent Identifierhttp://hdl.handle.net/10722/43499
ISSN
2015 Impact Factor: 2.78
2015 SCImago Journal Rankings: 6.653

 

DC FieldValueLanguage
dc.contributor.authorLee, SMSen_HK
dc.contributor.authorYoung, GAen_HK
dc.date.accessioned2007-03-23T04:47:15Z-
dc.date.available2007-03-23T04:47:15Z-
dc.date.issued1995en_HK
dc.identifier.citationAnnals of Statistics, 1995, v. 23 n. 4, p. 1301-1330en_HK
dc.identifier.issn0090-5364en_HK
dc.identifier.urihttp://hdl.handle.net/10722/43499-
dc.description.abstractAn iterated bootstrap confidence interval requires an additive correction to be made to the nominal coverage level of an uncorrected interval. Such correction is usually performed using a computationally intensive Monte Carlo simulation involving two nested levels of bootstrap sampling. Asymptotic expansions of the required correction and the iterated interval endpoints are used to provide two new computationally efficient methods for constructing an approximation to the iterated bootstrap confidence interval. The first asymptotic interval replaces the need for a second level of bootstrap sampling with a series of preliminary analytic calculations, which are readily automated, and from which an approximation to the coverage correction is easily obtained. The second interval directly approximates the endpoints of the iterated interval and yields, for the first time, the possibility of constructing an approximation to an iterated bootstrap confidence interval which does not require any resampling. The theoretical properties of the two intervals are considered. The computation required for their construction is detailed and has been coded in a fully automatic user-friendly Fortran program which may be obtained by anonymous ftp. A simulation study which illustrates their effectiveness on three examples is presented.en_HK
dc.format.extent2521744 bytes-
dc.format.extent26112 bytes-
dc.format.mimetypeapplication/pdf-
dc.format.mimetypeapplication/msword-
dc.languageengen_HK
dc.publisherInstitute of Mathematical Statistics.en_HK
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.subjectAsymptoticen_HK
dc.subjectBootstrapen_HK
dc.subjectCoverage erroren_HK
dc.subjectEdgeworth expansionen_HK
dc.subjectIterated bootstrapen_HK
dc.titleAsymptotic iterated bootstrap confidence intervalsen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0090-5364&volume=23&issue=4&spage=1301&epage=1330&date=1995&atitle=Asymptotic+iterated+bootstrap+confidence+intervalsen_HK
dc.description.naturepublished_or_final_versionen_HK
dc.identifier.hkuros11220-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats