Modelling overdispersion with integer-valued moving average processes

Detalhes bibliográficos
Autor(a) principal: Silva, Maria Eduarda
Data de Publicação: 2019
Outros Autores: Silva, Isabel, Torres, Cristina
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10773/26802
Resumo: A new first-order integer-valued moving average, INMA(1), model based on the negative binomial thinning operation defined by Risti´c et al. [21] is proposed and characterized. It is shown that this model has negative binomial (NB) marginal distribution when the innovations follow a NB distribution and therefore it can be used in situations where the data present overdispersion. Additionally, this model is extended to the bivariate context. The Generalized Method of Moments (GMM) is used to estimate the unknown parameters of the proposed models and the results of a simulation study that intends to investigate the performance of the method show that, in general, the estimates are consistent and symmetric. Finally, the proposed model is fitted to a real dataset and the quality of the adjustment is evaluated.
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spelling Modelling overdispersion with integer-valued moving average processesCount time seriesOverdispersionBivariate time seriesINAR modelsNegative binomialA new first-order integer-valued moving average, INMA(1), model based on the negative binomial thinning operation defined by Risti´c et al. [21] is proposed and characterized. It is shown that this model has negative binomial (NB) marginal distribution when the innovations follow a NB distribution and therefore it can be used in situations where the data present overdispersion. Additionally, this model is extended to the bivariate context. The Generalized Method of Moments (GMM) is used to estimate the unknown parameters of the proposed models and the results of a simulation study that intends to investigate the performance of the method show that, in general, the estimates are consistent and symmetric. Finally, the proposed model is fitted to a real dataset and the quality of the adjustment is evaluated.Springer International Publishing2019-032019-03-01T00:00:00Z2020-11-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10773/26802eng978-3-030-28664-42194-100910.1007/978-3-030-28665-1Silva, Maria EduardaSilva, IsabelTorres, Cristinainfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-02-22T11:51:52Zoai:ria.ua.pt:10773/26802Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T02:59:40.838809Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Modelling overdispersion with integer-valued moving average processes
title Modelling overdispersion with integer-valued moving average processes
spellingShingle Modelling overdispersion with integer-valued moving average processes
Silva, Maria Eduarda
Count time series
Overdispersion
Bivariate time series
INAR models
Negative binomial
title_short Modelling overdispersion with integer-valued moving average processes
title_full Modelling overdispersion with integer-valued moving average processes
title_fullStr Modelling overdispersion with integer-valued moving average processes
title_full_unstemmed Modelling overdispersion with integer-valued moving average processes
title_sort Modelling overdispersion with integer-valued moving average processes
author Silva, Maria Eduarda
author_facet Silva, Maria Eduarda
Silva, Isabel
Torres, Cristina
author_role author
author2 Silva, Isabel
Torres, Cristina
author2_role author
author
dc.contributor.author.fl_str_mv Silva, Maria Eduarda
Silva, Isabel
Torres, Cristina
dc.subject.por.fl_str_mv Count time series
Overdispersion
Bivariate time series
INAR models
Negative binomial
topic Count time series
Overdispersion
Bivariate time series
INAR models
Negative binomial
description A new first-order integer-valued moving average, INMA(1), model based on the negative binomial thinning operation defined by Risti´c et al. [21] is proposed and characterized. It is shown that this model has negative binomial (NB) marginal distribution when the innovations follow a NB distribution and therefore it can be used in situations where the data present overdispersion. Additionally, this model is extended to the bivariate context. The Generalized Method of Moments (GMM) is used to estimate the unknown parameters of the proposed models and the results of a simulation study that intends to investigate the performance of the method show that, in general, the estimates are consistent and symmetric. Finally, the proposed model is fitted to a real dataset and the quality of the adjustment is evaluated.
publishDate 2019
dc.date.none.fl_str_mv 2019-03
2019-03-01T00:00:00Z
2020-11-01T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10773/26802
url http://hdl.handle.net/10773/26802
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 978-3-030-28664-4
2194-1009
10.1007/978-3-030-28665-1
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Springer International Publishing
publisher.none.fl_str_mv Springer International Publishing
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
repository.mail.fl_str_mv
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