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dc.contributor.CRUESPUNIVERSIDADE DE ESTADUAL DE CAMPINASpt_BR
dc.typeArtigo de periódicopt_BR
dc.titleBayesian Inference On The Memory Parameter For Gamma-modulated Regression Modelspt_BR
dc.contributor.authorAndradept_BR
dc.contributor.authorPlinio; Rifopt_BR
dc.contributor.authorLaura; Torrespt_BR
dc.contributor.authorSoledad; Torres-Avilespt_BR
dc.contributor.authorFranciscopt_BR
unicamp.author.emailplinio@ime.usp.br; lramos@ime.unicamp.br; soledad.torres@uv.clpt_BR
unicamp.author[Rifo, Laura] Univ Estadual Campinas, Inst Math & Stat, BR-13083859 Campinas, SP, Brazilpt_BR
unicamp.author.external[Andrade, Plinio] Univ Sao Paulo, Inst Math & Stat, BR-05508090 Sao Paulo, Brazilpt
unicamp.author.external[Torres, Soledad] Univ Valparaiso, CIMFAV, Fac Ingn, Valparaiso 2362905, Chilept
unicamp.author.external[Torres-Aviles, Francisco] Univ Santiago Chile, Dept Matemat & Ciencia Comp, Santiago 9170022, Chilept
dc.subjectPhysics, Multidisciplinarypt_BR
dc.description.abstractIn this work, we propose a Bayesian methodology to make inferences for the memory parameter and other characteristics under non-standard assumptions for a class of stochastic processes. This class generalizes the Gamma-modulated process, with trajectories that exhibit long memory behavior, as well as decreasing variability as time increases. Different values of the memory parameter influence the speed of this decrease, making this heteroscedastic model very flexible. Its properties are used to implement an approximate Bayesian computation and MCMC scheme to obtain posterior estimates. We test and validate our method through simulations and real data from the big earthquake that occurred in 2010 in Chile.en
dc.relation.ispartofEntropypt_BR
dc.publisher.countryBASELpt_BR
dc.publisherMDPI AGpt_BR
dc.date.issued2015-OCTpt_BR
dc.identifier.citationBayesian Inference On The Memory Parameter For Gamma-modulated Regression Models. Mdpi Ag, v. 17, p. 6576-6597 OCT-2015.pt_BR
dc.language.isoenpt_BR
dc.description.volume17pt_BR
dc.description.issuenumber10pt_BR
dc.description.firstpage6576pt_BR
dc.description.lastpage6597pt_BR
dc.rightsabertopt_BR
dc.sourceWOSpt_BR
dc.identifier.issn1099-4300pt_BR
dc.identifier.wosidWOS:000364216800003pt_BR
dc.identifier.doi10.3390/e17106576pt_BR
dc.identifier.urlhttp://www.mdpi.com/1099-4300/17/10/6576pt_BR
dc.description.sponsorshipConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)pt_BR
dc.description.sponsorshipUniversity of Campinaspt_BR
dc.description.sponsorshipUniversidad de Santiago de Chilept_BR
dc.description.sponsorshipProject PROGRAMA INVESTIGACION ASOCIATIVA CONICYT Cuarto Concurso Nacional de Anillos de Investigacion en Ciencia y Tecnologiapt_BR
dc.description.sponsorshipRed de Analisis Estocastico y Aplicaciones (sistemas abiertos, energia y dinamica de la informacion) [ACT 1112]pt_BR
dc.description.sponsorshipFondecyt [1130586, 11110119]pt_BR
dc.description.sponsorshipInria Chile under project "Communication and information research & innovation center" [10CEII-9157]pt_BR
dc.description.sponsorshipFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)pt_BR
dc.description.sponsorship1Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)pt_BR
dc.description.sponsorship1Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)pt_BR
dc.description.sponsordocumentnumberCNPq [141048/2013-1]pt
dc.description.sponsordocumentnumberFAPESP [2013/07699-0]pt
dc.date.available2016-06-07T13:19:17Z-
dc.date.accessioned2016-06-07T13:19:17Z-
dc.description.provenanceMade available in DSpace on 2016-06-07T13:19:17Z (GMT). No. of bitstreams: 1 wos_000364216800003.pdf: 542982 bytes, checksum: 88acf227af47918c4d2de5126ce27ee4 (MD5) Previous issue date: 2015en
dc.identifier.urihttp://repositorio.unicamp.br/jspui/handle/REPOSIP/242647-
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