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Preliminary test of fit in a general class of conditionally heteroscedastic nonlinear time series

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dc.contributor.authorBaek, J. S.-
dc.contributor.authorPark, J. A.-
dc.contributor.authorHwang, S. Y.-
dc.date.available2021-02-22T13:02:33Z-
dc.date.issued2012-05-
dc.identifier.issn0094-9655-
dc.identifier.issn1563-5163-
dc.identifier.urihttps://scholarworks.sookmyung.ac.kr/handle/2020.sw.sookmyung/12363-
dc.description.abstractThis article is concerned with a general class of conditionally heteroscedastic time series including possibly nonlinear and asymmetric autoregressive conditional heteroscedastic (ARCH) and generalized ARCH models. A problem of preliminary test of fit (PTF, hereafter) within the broad class under consideration is discussed. It is noted that contrary to usual tests in the literature of conditionally heteroscedastic time series, PTF does not require any specification of the conditional variance in advance. Based on the joint limit distributions of sample autocorrelations, a certain Portmanteau-type statistic for PTF is proposed, and its limit is shown to be a chi-square distribution. In addition, some simulation studies, under various innovations, are reported to support our theoretical results.-
dc.format.extent19-
dc.language영어-
dc.language.isoENG-
dc.publisherTAYLOR & FRANCIS LTD-
dc.titlePreliminary test of fit in a general class of conditionally heteroscedastic nonlinear time series-
dc.typeArticle-
dc.publisher.location영국-
dc.identifier.doi10.1080/00949655.2011.558087-
dc.identifier.scopusid2-s2.0-84860125897-
dc.identifier.wosid000303235400008-
dc.identifier.bibliographicCitationJOURNAL OF STATISTICAL COMPUTATION AND SIMULATION, v.82, no.5, pp 763 - 781-
dc.citation.titleJOURNAL OF STATISTICAL COMPUTATION AND SIMULATION-
dc.citation.volume82-
dc.citation.number5-
dc.citation.startPage763-
dc.citation.endPage781-
dc.type.docTypeArticle-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaComputer Science-
dc.relation.journalResearchAreaMathematics-
dc.relation.journalWebOfScienceCategoryComputer Science, Interdisciplinary Applications-
dc.relation.journalWebOfScienceCategoryStatistics & Probability-
dc.subject.keywordPlusRESIDUAL AUTOCORRELATIONS-
dc.subject.keywordPlusVARIANCE-
dc.subject.keywordPlusMODELS-
dc.subject.keywordAuthorconditional heteroscedasticity-
dc.subject.keywordAuthornonlinear GARCH-
dc.subject.keywordAuthornonlinear time series-
dc.subject.keywordAuthorpreliminary test of fit-
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