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Article: Bootstrapping the portmanteau tests in weak auto-regressive moving average models

TitleBootstrapping the portmanteau tests in weak auto-regressive moving average models
Authors
KeywordsRandom-weighting approach
Portmanteau test
Weighted portmanteau test
Bootstrap method
Power generalized auto-regressive conditional heteroscedasticity models
Weak auto-regressive moving average models
Issue Date2016
Citation
Journal of the Royal Statistical Society. Series B: Statistical Methodology, 2016, v. 78, n. 2, p. 463-485 How to Cite?
Abstract© 2016 The Royal Statistical Society and Blackwell Publishing Ltd.The paper uses a random-weighting (RW) method to bootstrap the critical values for the Ljung-Box or Monti portmanteau tests and weighted Ljung-Box or Monti portmanteau tests in weak auto-regressive moving average models. Unlike the existing methods, no user-chosen parameter is needed to implement the RW method. As an application, these four tests are used to check the model adequacy in power generalized auto-regressive conditional heteroscedasticity models. Simulation evidence indicates that the weighted portmanteau tests have a power advantage over other existing tests. A real example on the Standard and Poor's 500 index illustrates the merits of our testing procedure. As an extension, the blockwise RW method is also studied.
Persistent Identifierhttp://hdl.handle.net/10722/231018
ISSN
2015 Impact Factor: 4.222
2015 SCImago Journal Rankings: 7.429

 

DC FieldValueLanguage
dc.contributor.authorZhu, Ke-
dc.date.accessioned2016-09-01T06:07:24Z-
dc.date.available2016-09-01T06:07:24Z-
dc.date.issued2016-
dc.identifier.citationJournal of the Royal Statistical Society. Series B: Statistical Methodology, 2016, v. 78, n. 2, p. 463-485-
dc.identifier.issn1369-7412-
dc.identifier.urihttp://hdl.handle.net/10722/231018-
dc.description.abstract© 2016 The Royal Statistical Society and Blackwell Publishing Ltd.The paper uses a random-weighting (RW) method to bootstrap the critical values for the Ljung-Box or Monti portmanteau tests and weighted Ljung-Box or Monti portmanteau tests in weak auto-regressive moving average models. Unlike the existing methods, no user-chosen parameter is needed to implement the RW method. As an application, these four tests are used to check the model adequacy in power generalized auto-regressive conditional heteroscedasticity models. Simulation evidence indicates that the weighted portmanteau tests have a power advantage over other existing tests. A real example on the Standard and Poor's 500 index illustrates the merits of our testing procedure. As an extension, the blockwise RW method is also studied.-
dc.languageeng-
dc.relation.ispartofJournal of the Royal Statistical Society. Series B: Statistical Methodology-
dc.subjectRandom-weighting approach-
dc.subjectPortmanteau test-
dc.subjectWeighted portmanteau test-
dc.subjectBootstrap method-
dc.subjectPower generalized auto-regressive conditional heteroscedasticity models-
dc.subjectWeak auto-regressive moving average models-
dc.titleBootstrapping the portmanteau tests in weak auto-regressive moving average models-
dc.typeArticle-
dc.description.natureLink_to_subscribed_fulltext-
dc.identifier.doi10.1111/rssb.12112-
dc.identifier.scopuseid_2-s2.0-84956594287-
dc.identifier.volume78-
dc.identifier.issue2-
dc.identifier.spage463-
dc.identifier.epage485-
dc.identifier.eissn1467-9868-

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