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Bayesian negative binomial regression with spatially varying dispersion: Modeling COVID-19 incidence in Georgia
Overdispersed count data arise commonly in disease mapping and infectious disease studies. Typically, the level of overdispersion is assumed to be constant over time and space. In some applications, however, this assumption is violated, and in such cases, it is necessary to model the dispersion as a...
| Autores principales: | , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Elsevier B.V.
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9500097/ https://www.ncbi.nlm.nih.gov/pubmed/36168515 http://dx.doi.org/10.1016/j.spasta.2022.100703 |