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Article: Arma modelling with non-Gaussian innovations

TitleArma modelling with non-Gaussian innovations
Authors
KeywordsAutoregressive moving-average process
Maximum likelihood estimation
Non-Gaussian innovations
Residual autocorrelations
Issue Date1988
PublisherBlackwell Publishing Ltd.
Citation
Journal of Time Series Analysis, 1988, v. 9 n. 2, p. 155-168 How to Cite?
AbstractThe problem of modelling time series driven by non-Gaussian innovations is considered. The asymptotic normality of the maximum likelihood estimator is established under some general conditions. The distribution of the residual autocorrelations is also obtained. This gives rise to a potentially useful goodness-of-fit statistic. Applications of the results to two important cases are discussed. Two real examples are considered.
Persistent Identifierhttp://hdl.handle.net/10722/130635
ISSN
2015 Impact Factor: 1.0
2015 SCImago Journal Rankings: 1.177

 

DC FieldValueLanguage
dc.contributor.authorLi, WK-
dc.contributor.authorMcLeod, AI-
dc.date.accessioned2010-12-30T08:16:09Z-
dc.date.available2010-12-30T08:16:09Z-
dc.date.issued1988-
dc.identifier.citationJournal of Time Series Analysis, 1988, v. 9 n. 2, p. 155-168-
dc.identifier.issn0143-9782-
dc.identifier.urihttp://hdl.handle.net/10722/130635-
dc.description.abstractThe problem of modelling time series driven by non-Gaussian innovations is considered. The asymptotic normality of the maximum likelihood estimator is established under some general conditions. The distribution of the residual autocorrelations is also obtained. This gives rise to a potentially useful goodness-of-fit statistic. Applications of the results to two important cases are discussed. Two real examples are considered.-
dc.languageeng-
dc.publisherBlackwell Publishing Ltd.-
dc.relation.ispartofJournal of Time Series Analysis-
dc.rightsJournal of Time Series Analysis. Copyright © Blackwell Publishing Ltd.-
dc.rightsThe definitive version is available at www.blackwell-synergy.com-
dc.subjectAutoregressive moving-average process-
dc.subjectMaximum likelihood estimation-
dc.subjectNon-Gaussian innovations-
dc.subjectResidual autocorrelations-
dc.titleArma modelling with non-Gaussian innovationsen_US
dc.typeArticleen_US
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0143-9782&volume=9&issue=2&spage=155–168&epage=&date=1988&atitle=Arma+modelling+with+non-Gaussian+innovations-
dc.identifier.emailLi, WK: hrntlwk@hkucc.hku.hk-
dc.identifier.doi10.1111/j.1467-9892.1988.tb00461.x-
dc.identifier.volume9-
dc.identifier.issue2-
dc.identifier.spage155-
dc.identifier.epage168-

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