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Article: Nonparametric likelihood ratio confidence intervals

TitleNonparametric likelihood ratio confidence intervals
Authors
KeywordsBootstrap
Coverage
Empirical likelihood
Least favourable family
Nonparametric likelihood
Issue Date1999
PublisherOxford University Press. The Journal's web site is located at http://biomet.oxfordjournals.org/
Citation
Biometrika, 1999, v. 86 n. 1, p. 107-118 How to Cite?
AbstractWe consider construction of two-sided nonparametric confidence intervals in a smooth function model setting. A nonparametric likelihood approach based on Stein's least favourable family is proposed as an alternative to empirical likelihood. The approach enjoys the same asymptotic properties as empirical likelihood, but is analytically and computationally less cumbersome. The simplicity of the method allows us to propose and analyse asymptotic and bootstrapping techniques as a means of reducing coverage error to levels comparable with those obtained by more computationally-intensive techniques such as the iterated bootstrap. A simulation study confirms that coverage error may be substantially reduced by simple analytic adjustment of the nonparametric likelihood interval and that bootstrapping the distribution of the nonparametric likelihood ratio results in very desirable coverage accuracy. © 1999 Biometrika Trust.
Persistent Identifierhttp://hdl.handle.net/10722/82721
ISSN
2015 Impact Factor: 1.13
2015 SCImago Journal Rankings: 2.801
References

 

DC FieldValueLanguage
dc.contributor.authorLee, SMSen_HK
dc.contributor.authorAlastair Young, Gen_HK
dc.date.accessioned2010-09-06T08:32:38Z-
dc.date.available2010-09-06T08:32:38Z-
dc.date.issued1999en_HK
dc.identifier.citationBiometrika, 1999, v. 86 n. 1, p. 107-118en_HK
dc.identifier.issn0006-3444en_HK
dc.identifier.urihttp://hdl.handle.net/10722/82721-
dc.description.abstractWe consider construction of two-sided nonparametric confidence intervals in a smooth function model setting. A nonparametric likelihood approach based on Stein's least favourable family is proposed as an alternative to empirical likelihood. The approach enjoys the same asymptotic properties as empirical likelihood, but is analytically and computationally less cumbersome. The simplicity of the method allows us to propose and analyse asymptotic and bootstrapping techniques as a means of reducing coverage error to levels comparable with those obtained by more computationally-intensive techniques such as the iterated bootstrap. A simulation study confirms that coverage error may be substantially reduced by simple analytic adjustment of the nonparametric likelihood interval and that bootstrapping the distribution of the nonparametric likelihood ratio results in very desirable coverage accuracy. © 1999 Biometrika Trust.en_HK
dc.languageengen_HK
dc.publisherOxford University Press. The Journal's web site is located at http://biomet.oxfordjournals.org/en_HK
dc.relation.ispartofBiometrikaen_HK
dc.rightsBiometrika. Copyright © Oxford University Press.en_HK
dc.subjectBootstrapen_HK
dc.subjectCoverageen_HK
dc.subjectEmpirical likelihooden_HK
dc.subjectLeast favourable familyen_HK
dc.subjectNonparametric likelihooden_HK
dc.titleNonparametric likelihood ratio confidence intervalsen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0006-3444&volume=86&spage=107&epage=118&date=1999&atitle=Nonparametric+likelihood+ratio+confidence+intervalsen_HK
dc.identifier.emailLee, SMS: smslee@hku.hken_HK
dc.identifier.authorityLee, SMS=rp00726en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.scopuseid_2-s2.0-15844430555en_HK
dc.identifier.hkuros62166en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-15844430555&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume86en_HK
dc.identifier.issue1en_HK
dc.identifier.spage107en_HK
dc.identifier.epage118en_HK
dc.publisher.placeUnited Kingdomen_HK
dc.identifier.scopusauthoridLee, SMS=24280225500en_HK
dc.identifier.scopusauthoridAlastair Young, G=7402900500en_HK

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