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Forecasting the patterns of COVID-19 and causal impacts of lockdown in top five affected countries using Bayesian Structural Time Series Models
BACKGROUND: There are numerous studies dealing with analysis for the future patterns of COVID-19 in different countries using conventional time series models. This study aims to provide more flexible analytical framework that decomposes the important components of the time series, incorporates the p...
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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Elsevier Ltd.
2020
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7420989/ https://www.ncbi.nlm.nih.gov/pubmed/32834662 http://dx.doi.org/10.1016/j.chaos.2020.110196 |