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dc.contributor.authorAhtola, Juha
dc.contributor.authorTiao, George C.
dc.date.accessioned2007-11-29T17:09:54Z
dc.date.available2007-11-29T17:09:54Z
dc.date.issued1984-12
dc.identifier.issn0210-8054 (versió paper)
dc.identifier.urihttp://hdl.handle.net/2099/3918
dc.description.abstractThis article will extend the discussion in Ahtola and Tiao (1984a) of the finite sample distribution of the score function in nearly nonstationary first order autoregressions to nearly noninvertible first order moving average models. This distribution theory can be used to appreciate the behavior of the score function in situations where the asymptotic normal theory is known to give poor approximations in finite samples. The approximate distributions suggested here can be used to test for the value of the moving average parameter when it is close to unity. In particular, a test for noninvertibility can be obtained with an exact finite sample distribution of the test statistic under the null hypothesis.
dc.format.extentp. 151-163
dc.language.isoeng
dc.publisherUniversitat Politècnica de Barcelona. Centre de Càlcul
dc.relation.ispartofQüestiió. 1984, vol. 8, núm. 4
dc.rightsAttribution-NonCommercial-NoDerivs 2.5 Spain
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/2.5/es/
dc.subject.otherInference
dc.subject.otherApproximate distribution
dc.subject.otherChi-square
dc.subject.otherFinite sample
dc.subject.otherInvertibility
dc.subject.otherMinimum eigenvalue
dc.subject.otherMoving average
dc.subject.otherNonnormality
dc.titleSome aspects of parameter inference for nearly nonstationary and nearly noninvertible ARMA Models II
dc.typeArticle
dc.subject.lemacInferència
dc.subject.lemacProcessos estocàstics
dc.subject.amsClassificació AMS::62 Statistics::62M Inference from stochastic processes
dc.rights.accessOpen Access
upcommons.ordre2


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Except where otherwise noted, content on this work is licensed under a Creative Commons license: Attribution-NonCommercial-NoDerivs 2.5 Spain