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A multivariate statistical approach to predict COVID‐19 count data with epidemiological interpretation and uncertainty quantification
For the analysis of COVID‐19 pandemic data, we propose Bayesian multinomial and Dirichlet‐multinomial autoregressive models for time‐series of counts of patients in mutually exclusive and exhaustive observational categories, defined according to the severity of the patient status and the required tr...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
John Wiley and Sons Inc.
2021
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8441832/ https://www.ncbi.nlm.nih.gov/pubmed/34374438 http://dx.doi.org/10.1002/sim.9129 |