Granger causality and time series regression for modelling the migratory dynamics of infuenza into Brazil

Detalhes bibliográficos
Autor(a) principal: Grande, Aline Foerster
Data de Publicação: 2023
Outros Autores: Pumi, Guilherme, Cybis, Gabriela Bettella
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UFRGS
Texto Completo: http://hdl.handle.net/10183/271783
Resumo: In this work we study the problem of modelling and forecasting the dynamics of the infuenza virus in Brazil at a given month, from data on reported cases and genetic diversity collected from previous months, in other locations. Granger causality is employed as a tool to assess possible predictive relationships between covariates. For modelling and forecasting purposes, a time series regression approach is applied considering lagged information regarding reported cases and genetic diversity in other regions. Three different models are analysed, including stepwise time series regression and LASSO.
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spelling Grande, Aline FoersterPumi, GuilhermeCybis, Gabriela Bettella2024-02-09T05:07:41Z20231696-2281http://hdl.handle.net/10183/271783001174042In this work we study the problem of modelling and forecasting the dynamics of the infuenza virus in Brazil at a given month, from data on reported cases and genetic diversity collected from previous months, in other locations. Granger causality is employed as a tool to assess possible predictive relationships between covariates. For modelling and forecasting purposes, a time series regression approach is applied considering lagged information regarding reported cases and genetic diversity in other regions. Three different models are analysed, including stepwise time series regression and LASSO.application/pdfengSORT (Statistics and Operations Research Transactions). spain, Barcelona Institut d'Estadística de Catalunya. Vol.46 (2022), p. 161-188GripeRegressao estatisticaSeleção de variáveisDiversidade genéticaCausalidadeFluTime series regression,Variable selectionGenetic diversityGranger causalityGranger causality and time series regression for modelling the migratory dynamics of infuenza into BrazilEstrangeiroinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFRGSinstname:Universidade Federal do Rio Grande do Sul (UFRGS)instacron:UFRGSTEXT001174042.pdf.txt001174042.pdf.txtExtracted Texttext/plain62572http://www.lume.ufrgs.br/bitstream/10183/271783/2/001174042.pdf.txtd0722b46c33ab60276d9ee608ec5c2cfMD52ORIGINAL001174042.pdfTexto completo (inglês)application/pdf901069http://www.lume.ufrgs.br/bitstream/10183/271783/1/001174042.pdf65d80da5de747c5759a49be45910f597MD5110183/2717832024-02-10 06:08:38.276936oai:www.lume.ufrgs.br:10183/271783Repositório de PublicaçõesPUBhttps://lume.ufrgs.br/oai/requestopendoar:2024-02-10T08:08:38Repositório Institucional da UFRGS - Universidade Federal do Rio Grande do Sul (UFRGS)false
dc.title.pt_BR.fl_str_mv Granger causality and time series regression for modelling the migratory dynamics of infuenza into Brazil
title Granger causality and time series regression for modelling the migratory dynamics of infuenza into Brazil
spellingShingle Granger causality and time series regression for modelling the migratory dynamics of infuenza into Brazil
Grande, Aline Foerster
Gripe
Regressao estatistica
Seleção de variáveis
Diversidade genética
Causalidade
Flu
Time series regression,
Variable selection
Genetic diversity
Granger causality
title_short Granger causality and time series regression for modelling the migratory dynamics of infuenza into Brazil
title_full Granger causality and time series regression for modelling the migratory dynamics of infuenza into Brazil
title_fullStr Granger causality and time series regression for modelling the migratory dynamics of infuenza into Brazil
title_full_unstemmed Granger causality and time series regression for modelling the migratory dynamics of infuenza into Brazil
title_sort Granger causality and time series regression for modelling the migratory dynamics of infuenza into Brazil
author Grande, Aline Foerster
author_facet Grande, Aline Foerster
Pumi, Guilherme
Cybis, Gabriela Bettella
author_role author
author2 Pumi, Guilherme
Cybis, Gabriela Bettella
author2_role author
author
dc.contributor.author.fl_str_mv Grande, Aline Foerster
Pumi, Guilherme
Cybis, Gabriela Bettella
dc.subject.por.fl_str_mv Gripe
Regressao estatistica
Seleção de variáveis
Diversidade genética
Causalidade
topic Gripe
Regressao estatistica
Seleção de variáveis
Diversidade genética
Causalidade
Flu
Time series regression,
Variable selection
Genetic diversity
Granger causality
dc.subject.eng.fl_str_mv Flu
Time series regression,
Variable selection
Genetic diversity
Granger causality
description In this work we study the problem of modelling and forecasting the dynamics of the infuenza virus in Brazil at a given month, from data on reported cases and genetic diversity collected from previous months, in other locations. Granger causality is employed as a tool to assess possible predictive relationships between covariates. For modelling and forecasting purposes, a time series regression approach is applied considering lagged information regarding reported cases and genetic diversity in other regions. Three different models are analysed, including stepwise time series regression and LASSO.
publishDate 2023
dc.date.issued.fl_str_mv 2023
dc.date.accessioned.fl_str_mv 2024-02-09T05:07:41Z
dc.type.driver.fl_str_mv Estrangeiro
info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10183/271783
dc.identifier.issn.pt_BR.fl_str_mv 1696-2281
dc.identifier.nrb.pt_BR.fl_str_mv 001174042
identifier_str_mv 1696-2281
001174042
url http://hdl.handle.net/10183/271783
dc.language.iso.fl_str_mv eng
language eng
dc.relation.ispartof.pt_BR.fl_str_mv SORT (Statistics and Operations Research Transactions). spain, Barcelona Institut d'Estadística de Catalunya. Vol.46 (2022), p. 161-188
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
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instname:Universidade Federal do Rio Grande do Sul (UFRGS)
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instname_str Universidade Federal do Rio Grande do Sul (UFRGS)
instacron_str UFRGS
institution UFRGS
reponame_str Repositório Institucional da UFRGS
collection Repositório Institucional da UFRGS
bitstream.url.fl_str_mv http://www.lume.ufrgs.br/bitstream/10183/271783/2/001174042.pdf.txt
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