Wavelet-Based Detection of Outliers in Poisson INAR(1) Time Series

Detalhes bibliográficos
Autor(a) principal: Isabel Silva
Data de Publicação: 2018
Outros Autores: Maria Eduarda Silva
Tipo de documento: Livro
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: https://hdl.handle.net/10216/111744
Resumo: The presence of outliers or discrepant observations has a negative impact in time series modelling. This paper considers the problem of detecting outliers, additive or innovational, single, multiple or in patches, in count time series modelled by first-order Poisson integer-valued autoregressive, PoINAR(1), models. To address this problem, two wavelet-based approaches that allow the identification of the time points of outlier occurrence are proposed. The effectiveness of the proposed methods is illustrated with synthetic as well as with an observed dataset.
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spelling Wavelet-Based Detection of Outliers in Poisson INAR(1) Time SeriesThe presence of outliers or discrepant observations has a negative impact in time series modelling. This paper considers the problem of detecting outliers, additive or innovational, single, multiple or in patches, in count time series modelled by first-order Poisson integer-valued autoregressive, PoINAR(1), models. To address this problem, two wavelet-based approaches that allow the identification of the time points of outlier occurrence are proposed. The effectiveness of the proposed methods is illustrated with synthetic as well as with an observed dataset.20182018-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/bookapplication/pdfhttps://hdl.handle.net/10216/111744eng10.1007/978-3-319-76605-8_13Isabel SilvaMaria Eduarda Silvainfo: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:RCAAP2023-11-29T13:54:31Zoai:repositorio-aberto.up.pt:10216/111744Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T23:50:26.917625Repositório 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 Wavelet-Based Detection of Outliers in Poisson INAR(1) Time Series
title Wavelet-Based Detection of Outliers in Poisson INAR(1) Time Series
spellingShingle Wavelet-Based Detection of Outliers in Poisson INAR(1) Time Series
Isabel Silva
title_short Wavelet-Based Detection of Outliers in Poisson INAR(1) Time Series
title_full Wavelet-Based Detection of Outliers in Poisson INAR(1) Time Series
title_fullStr Wavelet-Based Detection of Outliers in Poisson INAR(1) Time Series
title_full_unstemmed Wavelet-Based Detection of Outliers in Poisson INAR(1) Time Series
title_sort Wavelet-Based Detection of Outliers in Poisson INAR(1) Time Series
author Isabel Silva
author_facet Isabel Silva
Maria Eduarda Silva
author_role author
author2 Maria Eduarda Silva
author2_role author
dc.contributor.author.fl_str_mv Isabel Silva
Maria Eduarda Silva
description The presence of outliers or discrepant observations has a negative impact in time series modelling. This paper considers the problem of detecting outliers, additive or innovational, single, multiple or in patches, in count time series modelled by first-order Poisson integer-valued autoregressive, PoINAR(1), models. To address this problem, two wavelet-based approaches that allow the identification of the time points of outlier occurrence are proposed. The effectiveness of the proposed methods is illustrated with synthetic as well as with an observed dataset.
publishDate 2018
dc.date.none.fl_str_mv 2018
2018-01-01T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/book
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status_str publishedVersion
dc.identifier.uri.fl_str_mv https://hdl.handle.net/10216/111744
url https://hdl.handle.net/10216/111744
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1007/978-3-319-76605-8_13
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.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
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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
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