File Download
  Links for fulltext
     (May Require Subscription)
Supplementary

Article: Nonparametric conditional inference for regression coefficients with application to configural polysampling

TitleNonparametric conditional inference for regression coefficients with application to configural polysampling
Authors
KeywordsAncillary
Bandwidth
Conditional inference
Configural polysampling
Confrontation
Plug-in
Issue Date2008
PublisherAcademia Sinica, Institute of Statistical Science. The Journal's web site is located at http://www.stat.sinica.edu.tw/statistica/
Citation
Statistica Sinica, 2008, v. 18 n. 1, p. 155-169 How to Cite?
AbstractWe consider inference procedures, conditional on an observed ancillary statistic, for regression coefficients under a linear regression setup where the unknown error distribution is specified nonparametrically. We establish conditional asymptotic normality of the regression coefficient estimators under regularity conditions, and formally justify the approach of plugging in kernel-type density estimators in conditional inference procedures. Simulation results show that the approach yields accurate conditional coverage probabilities when used for constructing confidence intervals. The plug-in approach can be applied in conjunction with configural polysampling to derive robust conditional estimators adaptive to a confrontation of contrasting scenarios. We demonstrate this by investigating the conditional mean squared error of location estimators under various confrontations in a simulation study, which successfully extends configural polysampling to a nonparametric context.
Persistent Identifierhttp://hdl.handle.net/10722/57161
ISSN
2015 Impact Factor: 0.838
2015 SCImago Journal Rankings: 2.292

 

DC FieldValueLanguage
dc.contributor.authorHo, YHSen_HK
dc.contributor.authorLee, SMSen_HK
dc.date.accessioned2010-04-12T01:27:54Z-
dc.date.available2010-04-12T01:27:54Z-
dc.date.issued2008en_HK
dc.identifier.citationStatistica Sinica, 2008, v. 18 n. 1, p. 155-169en_HK
dc.identifier.issn1017-0405en_HK
dc.identifier.urihttp://hdl.handle.net/10722/57161-
dc.description.abstractWe consider inference procedures, conditional on an observed ancillary statistic, for regression coefficients under a linear regression setup where the unknown error distribution is specified nonparametrically. We establish conditional asymptotic normality of the regression coefficient estimators under regularity conditions, and formally justify the approach of plugging in kernel-type density estimators in conditional inference procedures. Simulation results show that the approach yields accurate conditional coverage probabilities when used for constructing confidence intervals. The plug-in approach can be applied in conjunction with configural polysampling to derive robust conditional estimators adaptive to a confrontation of contrasting scenarios. We demonstrate this by investigating the conditional mean squared error of location estimators under various confrontations in a simulation study, which successfully extends configural polysampling to a nonparametric context.en_HK
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.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.subjectAncillaryen_HK
dc.subjectBandwidthen_HK
dc.subjectConditional inferenceen_HK
dc.subjectConfigural polysamplingen_HK
dc.subjectConfrontationen_HK
dc.subjectPlug-inen_HK
dc.titleNonparametric conditional inference for regression coefficients with application to configural polysamplingen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=1017-0405&volume=18&issue=1&spage=155&epage=169&date=2008&atitle=Nonparametric+conditional+inference+for+regression+coefficients+with+application+to+configural+polysamplingen_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-s2.0-43049120311en_HK
dc.identifier.hkuros150491-
dc.identifier.volume18en_HK
dc.identifier.issue1en_HK
dc.identifier.spage155en_HK
dc.identifier.epage169en_HK
dc.publisher.placeTaiwan, Republic of Chinaen_HK
dc.identifier.scopusauthoridHo, YHS=8378552000en_HK
dc.identifier.scopusauthoridLee, SMS=24280225500en_HK

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats