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Bayesian non-parametric inference for stochastic epidemic models using Gaussian Processes
This paper considers novel Bayesian non-parametric methods for stochastic epidemic models. Many standard modeling and data analysis methods use underlying assumptions (e.g. concerning the rate at which new cases of disease will occur) which are rarely challenged or tested in practice. To relax these...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Oxford University Press
2016
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5031942/ https://www.ncbi.nlm.nih.gov/pubmed/26993062 http://dx.doi.org/10.1093/biostatistics/kxw011 |