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Article: First-order rounded integer-valued autoregressive (RINAR(1)) process

TitleFirst-order rounded integer-valued autoregressive (RINAR(1)) process
Authors
KeywordsINAR models
Integer-valued time series
Least squares estimator
RINAR(1) model
Rounding operator
Issue Date2009
PublisherBlackwell Publishing Ltd
Citation
Journal Of Time Series Analysis, 2009, v. 30 n. 4, p. 417-448 How to Cite?
AbstractWe introduce a new class of autoregressive models for integer-valued time series using the rounding operator. Compared with classical INAR models based on the thinning operator, the new models have several advantages: simple innovation structure, autoregressive coefficients with arbitrary signs, possible negative values for time series and possible negative values for the autocorrelation function. Focused on the first-order RINAR(1) model, we give conditions for its ergodicity and stationarity. For parameter estimation, a least squares estimator is introduced and we prove its consistency under suitable identifiability condition. Simulation experiments as well as analysis of real data sets are carried out to attest the model performance. © 2009 Blackwell Publishing Ltd.
Persistent Identifierhttp://hdl.handle.net/10722/132606
ISSN
2015 Impact Factor: 1.0
2015 SCImago Journal Rankings: 1.177
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorKachour, Men_HK
dc.contributor.authorYao, JFen_HK
dc.date.accessioned2011-03-28T09:26:58Z-
dc.date.available2011-03-28T09:26:58Z-
dc.date.issued2009en_HK
dc.identifier.citationJournal Of Time Series Analysis, 2009, v. 30 n. 4, p. 417-448en_HK
dc.identifier.issn0143-9782en_HK
dc.identifier.urihttp://hdl.handle.net/10722/132606-
dc.description.abstractWe introduce a new class of autoregressive models for integer-valued time series using the rounding operator. Compared with classical INAR models based on the thinning operator, the new models have several advantages: simple innovation structure, autoregressive coefficients with arbitrary signs, possible negative values for time series and possible negative values for the autocorrelation function. Focused on the first-order RINAR(1) model, we give conditions for its ergodicity and stationarity. For parameter estimation, a least squares estimator is introduced and we prove its consistency under suitable identifiability condition. Simulation experiments as well as analysis of real data sets are carried out to attest the model performance. © 2009 Blackwell Publishing Ltd.en_HK
dc.languageengen_US
dc.publisherBlackwell Publishing Ltden_US
dc.relation.ispartofJournal of Time Series Analysisen_HK
dc.subjectINAR modelsen_HK
dc.subjectInteger-valued time seriesen_HK
dc.subjectLeast squares estimatoren_HK
dc.subjectRINAR(1) modelen_HK
dc.subjectRounding operatoren_HK
dc.titleFirst-order rounded integer-valued autoregressive (RINAR(1)) processen_HK
dc.typeArticleen_HK
dc.identifier.emailYao, JF: jeffyao@hku.hken_HK
dc.identifier.authorityYao, JF=rp01473en_HK
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.doi10.1111/j.1467-9892.2009.00620.xen_HK
dc.identifier.scopuseid_2-s2.0-67650673066en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-67650673066&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume30en_HK
dc.identifier.issue4en_HK
dc.identifier.spage417en_HK
dc.identifier.epage448en_HK
dc.identifier.eissn1467-9892-
dc.identifier.isiWOS:000267173300003-
dc.publisher.placeUnited Kingdomen_HK
dc.identifier.scopusauthoridKachour, M=27867821400en_HK
dc.identifier.scopusauthoridYao, JF=7403503451en_HK
dc.identifier.citeulike4944714-

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