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Article: On m out of n bootstrapping for nonstandard M-estimation with nuisance parameters

TitleOn m out of n bootstrapping for nonstandard M-estimation with nuisance parameters
Authors
KeywordsGaussian process
M out of n bootstrap
M-estimator
Nuisance parameter
Subsampling
Issue Date2006
PublisherAmerican Statistical Association. The Journal's web site is located at http://www.amstat.org/publications/jasa/index.cfm?fuseaction=main
Citation
Journal Of The American Statistical Association, 2006, v. 101 n. 475, p. 1185-1197 How to Cite?
AbstractNonstandard M-estimation, with nuisance parameters consistently estimated in the criterion function, often yields M-estimators converging weakly at rates different from n1/2 with weak limits that are typically non-Gaussian. The complicated asymptotics involved makes distributional estimation of the M-estimators analytically prohibitive. We show that the problem is resolved by m out of n bootstrapping under very general conditions, which provides a universal and convenient approach to consistently estimating sampling distributions of M-estimators. We illustrate our findings with applications to least median of squares regression estimators, studentized location M-estimators, shorth estimators, and robust M-estimators derived from L r-type loss functions. We provide empirical evidence using a simulation study to construct confidence intervals and globally estimate sampling distributions. © 2006 American Statistical Association.
Persistent Identifierhttp://hdl.handle.net/10722/82875
ISSN
2015 Impact Factor: 1.725
2015 SCImago Journal Rankings: 3.447
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorLee, SMSen_HK
dc.contributor.authorPun, MCen_HK
dc.date.accessioned2010-09-06T08:34:24Z-
dc.date.available2010-09-06T08:34:24Z-
dc.date.issued2006en_HK
dc.identifier.citationJournal Of The American Statistical Association, 2006, v. 101 n. 475, p. 1185-1197en_HK
dc.identifier.issn0162-1459en_HK
dc.identifier.urihttp://hdl.handle.net/10722/82875-
dc.description.abstractNonstandard M-estimation, with nuisance parameters consistently estimated in the criterion function, often yields M-estimators converging weakly at rates different from n1/2 with weak limits that are typically non-Gaussian. The complicated asymptotics involved makes distributional estimation of the M-estimators analytically prohibitive. We show that the problem is resolved by m out of n bootstrapping under very general conditions, which provides a universal and convenient approach to consistently estimating sampling distributions of M-estimators. We illustrate our findings with applications to least median of squares regression estimators, studentized location M-estimators, shorth estimators, and robust M-estimators derived from L r-type loss functions. We provide empirical evidence using a simulation study to construct confidence intervals and globally estimate sampling distributions. © 2006 American Statistical Association.en_HK
dc.languageengen_HK
dc.publisherAmerican Statistical Association. The Journal's web site is located at http://www.amstat.org/publications/jasa/index.cfm?fuseaction=mainen_HK
dc.relation.ispartofJournal of the American Statistical Associationen_HK
dc.subjectGaussian processen_HK
dc.subjectM out of n bootstrapen_HK
dc.subjectM-estimatoren_HK
dc.subjectNuisance parameteren_HK
dc.subjectSubsamplingen_HK
dc.titleOn m out of n bootstrapping for nonstandard M-estimation with nuisance parametersen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0162-1459&volume=101&spage=1185&epage=1197&date=2006&atitle=On+m+out+of+n+bootstrapping+for+nonstandard+M-estimation+with+nuisance+parametersen_HK
dc.identifier.emailLee, SMS: smslee@hku.hken_HK
dc.identifier.authorityLee, SMS=rp00726en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1198/016214506000000014en_HK
dc.identifier.scopuseid_2-s2.0-33748882127en_HK
dc.identifier.hkuros124254en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-33748882127&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume101en_HK
dc.identifier.issue475en_HK
dc.identifier.spage1185en_HK
dc.identifier.epage1197en_HK
dc.identifier.eissn1537-274X-
dc.identifier.isiWOS:000240158700034-
dc.publisher.placeUnited Statesen_HK
dc.identifier.scopusauthoridLee, SMS=24280225500en_HK
dc.identifier.scopusauthoridPun, MC=14625683300en_HK
dc.identifier.citeulike894885-

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