Analysis of count time series: a bayesian GARMA(p, q) approach

Registro completo de metadados
MetadadosDescriçãoIdioma
Autor(es): dc.creatorPala, Luiz Otávio de Oliveira-
Autor(es): dc.creatorCarvalho, Marcela de M.-
Autor(es): dc.creatorSáfadi, Thelma-
Data de aceite: dc.date.accessioned2026-02-09T12:00:58Z-
Data de disponibilização: dc.date.available2026-02-09T12:00:58Z-
Data de envio: dc.date.issued2025-01-30-
Data de envio: dc.date.issued2025-01-30-
Data de envio: dc.date.issued2022-
Fonte completa do material: dc.identifierhttps://repositorio.ufla.br/handle/1/59806-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/capes/1152490-
Descrição: dc.descriptionExtensions of the Autoregressive Moving Average, ARMA(p, q), class for modeling non-Gaussian time series have been proposed in the literature in recent years, being applied in phenomena such as counts and rates. One of them is the Generalized Autoregressive Moving Average, GARMA(p, q), that is supported by the Generalized Linear Models theory and has been studied under the Bayesian perspective. This paper aimed to study models for time series of counts using the Poisson, Negative binomial and Poisson inverse Gaussian distributions, and adopting the Bayesian framework. To do so, we carried out a simulation study and, in addition, we showed a practical application and evaluation of these models by using a set of real data, corresponding to the number of vehicle thefts in Brazil.-
Formato: dc.formatapplication/pdf-
Idioma: dc.languageen-
Publicador: dc.publisherAustrian Society for Statistics-
Direitos: dc.rightsAttribution 4.0 International-
Direitos: dc.rightsAttribution 4.0 International-
Direitos: dc.rightsacesso aberto-
Direitos: dc.rightshttp://creativecommons.org/licenses/by/4.0/-
Direitos: dc.rightshttp://creativecommons.org/licenses/by/4.0/-
???dc.source???: dc.sourceAustrian Journal of Statistics-
Palavras-chave: dc.subjectAutoregressive moving average models-
Palavras-chave: dc.subjectCount data-
Palavras-chave: dc.subjectGeneralized linear models-
Palavras-chave: dc.subjectMarkov chain Monte Carlo (MCMC)-
Palavras-chave: dc.subjectTime series-
Título: dc.titleAnalysis of count time series: a bayesian GARMA(p, q) approach-
Tipo de arquivo: dc.typeArtigo-
Aparece nas coleções:Repositório Institucional da Universidade Federal de Lavras (RIUFLA)

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