Granger causality and time series regression for modelling the migratory dynamics of infuenza into Brazil
dc.contributor.author | Grande, Aline Foerster | pt_BR |
dc.contributor.author | Pumi, Guilherme | pt_BR |
dc.contributor.author | Cybis, Gabriela Bettella | pt_BR |
dc.date.accessioned | 2024-02-09T05:07:41Z | pt_BR |
dc.date.issued | 2023 | pt_BR |
dc.identifier.issn | 1696-2281 | pt_BR |
dc.identifier.uri | http://hdl.handle.net/10183/271783 | pt_BR |
dc.description.abstract | 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. | en |
dc.format.mimetype | application/pdf | pt_BR |
dc.language.iso | eng | pt_BR |
dc.relation.ispartof | SORT (Statistics and Operations Research Transactions). spain, Barcelona Institut d'Estadística de Catalunya. Vol.46 (2022), p. 161-188 | pt_BR |
dc.rights | Open Access | en |
dc.subject | Gripe | pt_BR |
dc.subject | Flu | en |
dc.subject | Regressao estatistica | pt_BR |
dc.subject | Time series regression, | en |
dc.subject | Seleção de variáveis | pt_BR |
dc.subject | Variable selection | en |
dc.subject | Genetic diversity | en |
dc.subject | Diversidade genética | pt_BR |
dc.subject | Causalidade | pt_BR |
dc.subject | Granger causality | en |
dc.title | Granger causality and time series regression for modelling the migratory dynamics of infuenza into Brazil | pt_BR |
dc.type | Artigo de periódico | pt_BR |
dc.identifier.nrb | 001174042 | pt_BR |
dc.type.origin | Estrangeiro | pt_BR |
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