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Article: Hysteretic autoregressive time series models

TitleHysteretic autoregressive time series models
Authors
Issue Date2015
PublisherOxford University Press. The Journal's web site is located at http://biomet.oxfordjournals.org/
Citation
Biometrika, 2015, v. 102 n. 3, p. 717-723 How to Cite?
AbstractThis paper extends the classical two-regime threshold autoregressive model by introducing hysteresis to its regime-switching structure, which leads to a new model: the hysteretic autoregressive model. The proposed model enjoys the piecewise linear structure of a threshold model but has a more flexible regime switching mechanism. A sufficient condition is given for geometric ergodicity. Conditional least squares estimation is discussed, and the asymptotic distributions of its estimators and information criteria for model selection are derived. Simulation results and an example support the model.
Persistent Identifierhttp://hdl.handle.net/10722/217204
ISSN
2015 Impact Factor: 1.13
2015 SCImago Journal Rankings: 2.801
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorLi, G-
dc.contributor.authorGuan, B-
dc.contributor.authorLi, WK-
dc.contributor.authorYu, PLH-
dc.date.accessioned2015-09-18T05:52:10Z-
dc.date.available2015-09-18T05:52:10Z-
dc.date.issued2015-
dc.identifier.citationBiometrika, 2015, v. 102 n. 3, p. 717-723-
dc.identifier.issn0006-3444-
dc.identifier.urihttp://hdl.handle.net/10722/217204-
dc.description.abstractThis paper extends the classical two-regime threshold autoregressive model by introducing hysteresis to its regime-switching structure, which leads to a new model: the hysteretic autoregressive model. The proposed model enjoys the piecewise linear structure of a threshold model but has a more flexible regime switching mechanism. A sufficient condition is given for geometric ergodicity. Conditional least squares estimation is discussed, and the asymptotic distributions of its estimators and information criteria for model selection are derived. Simulation results and an example support the model.-
dc.languageeng-
dc.publisherOxford University Press. The Journal's web site is located at http://biomet.oxfordjournals.org/-
dc.relation.ispartofBiometrika-
dc.rightsThis is a pre-copy-editing, author-produced PDF of an article accepted for publication in Biometrika following peer review. The definitive publisher-authenticated version Biometrika, 2015, v. 102 n. 3, p. 717-723 is available online at: http://biomet.oxfordjournals.org/content/102/3/717-
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.titleHysteretic autoregressive time series models-
dc.typeArticle-
dc.identifier.emailLi, G: gdli@hku.hk-
dc.identifier.emailLi, WK: hrntlwk@hkucc.hku.hk-
dc.identifier.emailYu, PLH: plhyu@hku.hk-
dc.identifier.authorityLi, G=rp00738-
dc.identifier.authorityLi, WK=rp00741-
dc.identifier.authorityYu, PLH=rp00835-
dc.description.naturepostprint-
dc.identifier.doi10.1093/biomet/asv017-
dc.identifier.scopuseid_2-s2.0-84941644328-
dc.identifier.hkuros250506-
dc.identifier.volume102-
dc.identifier.issue3-
dc.identifier.spage717-
dc.identifier.epage723-
dc.identifier.isiWOS:000361457200017-
dc.publisher.placeUnited Kingdom-

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