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Count‐valued time series models for COVID‐19 daily death dynamics
We propose a generalized non‐linear state‐space model for count‐valued time series of COVID‐19 fatalities. To capture the dynamic changes in daily COVID‐19 death counts, we specify a latent state process that involves second‐order differencing and an AR(1)‐ARCH(1) model. These modelling choices are...
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| Publicado no: | Stat (Int Stat Inst) |
|---|---|
| Main Authors: | , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
John Wiley and Sons Inc.
2021
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7995040/ https://ncbi.nlm.nih.gov/pubmed/33786170 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1002/sta4.369 |
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