Please use this identifier to cite or link to this item: http://hdl.handle.net/10773/26341
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dc.contributor.authorSantos, Cláudiapt_PT
dc.contributor.authorPereira, Isabelpt_PT
dc.contributor.authorScotto, Manuelpt_PT
dc.date.accessioned2019-07-31T15:25:23Z-
dc.date.available2019-07-31T15:25:23Z-
dc.date.issued2019-07-
dc.identifier.isbn978-3-030-24301-2pt_PT
dc.identifier.urihttp://hdl.handle.net/10773/26341-
dc.description.abstractIn this paper, an integer-valued autoregressive model of order one (INAR(1)) with time-varying parameters and driven by a periodic sequence of innovations is introduced. The proposed INAR(1) model is based on the signed thinning operator defined by Kachour and Truquet (2011) and conveniently adapted to the periodic case. Basic notations and definitions concerning the periodic signed thinning operator are provided. Based on this thinning operator, Chesneau and Kachour (2012) established a signed INAR(1) model. Motivated by the work of Chesneau and Kachour (2012), we introduce a periodic model, denoted by S-PINAR(1), with period s. In contrast to conventional INAR(1) models, these models are defined in Z allowing for negative values both for the series and its autocorrelation function. For a proper Z-valued time series, a distribution for the innovation term defined on Z is required. The S-PINAR(1) model assumes a specific innovation distribution, the Skellam distribution. Regarding parameter estimation, two methods are considered: conditional least squares and conditional maximum likelihood. The performance of the S-PINAR(1) model is assessed through a simulation study.pt_PT
dc.language.isoengpt_PT
dc.publisherSpringerpt_PT
dc.relationUID/MAT/04106/2019pt_PT
dc.relationUID/Multi/04621/2019pt_PT
dc.rightsrestrictedAccesspt_PT
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectInteger-valued autoregressive modelspt_PT
dc.subjectSigned thinning operatorpt_PT
dc.subjectSkellam distributionpt_PT
dc.titlePeriodic INAR(1) Models with Skellam-Distributed Innovationspt_PT
dc.typebookPartpt_PT
dc.description.versionpublishedpt_PT
dc.peerreviewedyespt_PT
degois.publication.firstPage64pt_PT
degois.publication.lastPage78pt_PT
degois.publication.locationChampt_PT
degois.publication.titleComputational Science and Its Applications – ICCSA 2019. ICCSA 2019. Lecture Notes in Computer Sciencept_PT
dc.relation.publisherversionhttps://link.springer.com/chapter/10.1007%2F978-3-030-24302-9_6pt_PT
dc.identifier.doi10.1007/978-3-030-24302-9_6pt_PT
dc.identifier.esbn978-3-030-24302-9pt_PT
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