Semiparametric inference with a functional-form empirical likelihood

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dc.contributor.authorChen, Sixiako
dc.contributor.authorKim, Jae Kwangko
dc.date.accessioned2016-10-04T02:57:20Z-
dc.date.available2016-10-04T02:57:20Z-
dc.date.created2016-09-08-
dc.date.created2016-09-08-
dc.date.issued2014-06-
dc.identifier.citationJOURNAL OF THE KOREAN STATISTICAL SOCIETY, v.43, no.2, pp.201 - 214-
dc.identifier.issn1226-3192-
dc.identifier.urihttp://hdl.handle.net/10203/212996-
dc.description.abstractA functional-form empirical likelihood method is proposed as an alternative method to the empirical likelihood method. The proposed method has the same asymptotic properties as the empirical likelihood method but has more flexibility in choosing the weight construction. Because it enjoys the likelihood-based interpretation, the profile likelihood ratio test can easily be constructed with a chi-square limiting distribution. Some computational details are also discussed, and results from finite-sample simulation studies are presented. (C) 2013 The Korean Statistical Society. Published by Elsevier B.V. All rights reserved-
dc.languageEnglish-
dc.publisherKOREAN STATISTICAL SOC-
dc.subjectGENERALIZED-METHOD-
dc.subjectMOMENTS ESTIMATORS-
dc.subjectLARGE-SAMPLE-
dc.subjectINFORMATION-
dc.subjectMODELS-
dc.subjectTESTS-
dc.titleSemiparametric inference with a functional-form empirical likelihood-
dc.typeArticle-
dc.identifier.wosid000335281700004-
dc.identifier.scopusid2-s2.0-84881419030-
dc.type.rimsART-
dc.citation.volume43-
dc.citation.issue2-
dc.citation.beginningpage201-
dc.citation.endingpage214-
dc.citation.publicationnameJOURNAL OF THE KOREAN STATISTICAL SOCIETY-
dc.identifier.doi10.1016/j.jkss.2013.07.005-
dc.contributor.localauthorKim, Jae Kwang-
dc.contributor.nonIdAuthorChen, Sixia-
dc.type.journalArticleArticle-
dc.subject.keywordAuthorExponential tilting-
dc.subject.keywordAuthorGeneralized method of moments-
dc.subject.keywordAuthorNonparametric maximum likelihood method-
dc.subject.keywordAuthorProfile likelihood ratio test-
dc.subject.keywordPlusGENERALIZED-METHOD-
dc.subject.keywordPlusMOMENTS ESTIMATORS-
dc.subject.keywordPlusLARGE-SAMPLE-
dc.subject.keywordPlusINFORMATION-
dc.subject.keywordPlusMODELS-
dc.subject.keywordPlusTESTS-
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