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On weak dependence conditions for Poisson autoregressions

dc.contributor.authorDoukhan, P.en
dc.contributor.authorFokianos, Konstantinosen
dc.contributor.authorTjøstheim, D.en
dc.creatorDoukhan, P.en
dc.creatorFokianos, Konstantinosen
dc.creatorTjøstheim, D.en
dc.date.accessioned2019-12-02T10:34:54Z
dc.date.available2019-12-02T10:34:54Z
dc.date.issued2012
dc.identifier.urihttp://gnosis.library.ucy.ac.cy/handle/7/56761
dc.description.abstractWe consider generalized linear models for regression modeling of count time series. We give easily verifiable conditions for obtaining weak dependence for such models. These results enable the development of maximum likelihood inference under minimal conditions. Some examples which are useful to applications are discussed in detail. © 2012 Elsevier B.V..en
dc.sourceStatistics and Probability Lettersen
dc.source.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84857279824&doi=10.1016%2fj.spl.2012.01.015&partnerID=40&md5=b4751c15f7405bdb125b5102b604c63c
dc.subjectAutocorrelationen
dc.subjectStationarityen
dc.subjectLimit theoremsen
dc.subjectGeneralized linear modelsen
dc.subjectPredictionen
dc.titleOn weak dependence conditions for Poisson autoregressionsen
dc.typeinfo:eu-repo/semantics/article
dc.identifier.doi10.1016/j.spl.2012.01.015
dc.description.volume82
dc.description.issue5
dc.description.startingpage942
dc.description.endingpage948
dc.author.facultyΣχολή Θετικών και Εφαρμοσμένων Επιστημών / Faculty of Pure and Applied Sciences
dc.author.departmentΤμήμα Μαθηματικών και Στατιστικής / Department of Mathematics and Statistics
dc.type.uhtypeArticleen
dc.description.notes<p>Cited By :32</p>en
dc.source.abbreviationStat.Probab.Lett.en
dc.contributor.orcidFokianos, Konstantinos [0000-0002-0051-711X]
dc.gnosis.orcid0000-0002-0051-711X


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