Bayesian Probabilistic Reasoning Applied to Mathematical Epidemiology for Predictive Spatiotemporal Analysis of Infectious Diseases
Abstract Probabilistic reasoning under uncertainty suits well to analysis of disease dynamics. The stochastic nature of disease progression is modeled by applying the principles of Bayesian learning. Bayesian learning predicts the disease progression, including prevalence and incidence, for a geogr...
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| Format: | Others |
| Language: | English |
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University of North Texas
2006
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| Online Access: | https://digital.library.unt.edu/ark:/67531/metadc5302/ |