Granger causality and time series regression for modelling the migratory dynamics of infuenza into Brazil
Autor(a) principal: | |
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Data de Publicação: | 2023 |
Outros Autores: | , |
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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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 |
dc.source.none.fl_str_mv |
reponame:Repositório Institucional da UFRGS instname:Universidade Federal do Rio Grande do Sul (UFRGS) instacron:UFRGS |
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Universidade Federal do Rio Grande do Sul (UFRGS) |
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UFRGS |
institution |
UFRGS |
reponame_str |
Repositório Institucional da UFRGS |
collection |
Repositório Institucional da UFRGS |
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