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Conference Paper: An application of the RINAR(1) process

TitleAn application of the RINAR(1) process
Authors
KeywordsInar Models
Integer-Valued Time Series
Least Squares Estimator
Rinar(1) Model
Rounding Operator
Issue Date2009
Citation
Ifac Proceedings Volumes (Ifac-Papersonline), 2009, v. 15 PART 1, p. 1441-1444 How to Cite?
AbstractWe introduce a new class of autoregressive models for integervalued time series using the rounding operator. Compared to 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; 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. An analysis of real data set is carried out to access the performance of the model. © 2009 IFAC.
Persistent Identifierhttp://hdl.handle.net/10722/173564
ISSN
References

 

DC FieldValueLanguage
dc.contributor.authorKachour, Men_US
dc.contributor.authorYao, JFen_US
dc.date.accessioned2012-10-30T06:33:12Z-
dc.date.available2012-10-30T06:33:12Z-
dc.date.issued2009en_US
dc.identifier.citationIfac Proceedings Volumes (Ifac-Papersonline), 2009, v. 15 PART 1, p. 1441-1444en_US
dc.identifier.issn1474-6670en_US
dc.identifier.urihttp://hdl.handle.net/10722/173564-
dc.description.abstractWe introduce a new class of autoregressive models for integervalued time series using the rounding operator. Compared to 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; 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. An analysis of real data set is carried out to access the performance of the model. © 2009 IFAC.en_US
dc.languageengen_US
dc.relation.ispartofIFAC Proceedings Volumes (IFAC-PapersOnline)en_US
dc.subjectInar Modelsen_US
dc.subjectInteger-Valued Time Seriesen_US
dc.subjectLeast Squares Estimatoren_US
dc.subjectRinar(1) Modelen_US
dc.subjectRounding Operatoren_US
dc.titleAn application of the RINAR(1) processen_US
dc.typeConference_Paperen_US
dc.identifier.emailYao, JF: jeffyao@hku.hken_US
dc.identifier.authorityYao, JF=rp01473en_US
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.doi10.3182/20090706-3-FR-2004.0373en_US
dc.identifier.scopuseid_2-s2.0-80051625412en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-80051625412&selection=ref&src=s&origin=recordpageen_US
dc.identifier.volume15en_US
dc.identifier.issuePART 1en_US
dc.identifier.spage1441en_US
dc.identifier.epage1444en_US
dc.identifier.scopusauthoridKachour, M=27867821400en_US
dc.identifier.scopusauthoridYao, JF=7403503451en_US

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