Bayesian Inference for Stochastic Epidemic Models using Markov chain Monte Carlo Methods
This thesis is concerned with statistical methodology for the analysis of stochastic SIR (Susceptible->Infective->Removed) epidemic models. We adopt the Bayesian paradigm and we develop suitably tailored Markov chain Monte Carlo (MCMC) algorithms. The focus is on methods that are easy to gener...
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| Format: | Thesis (University of Nottingham only) |
| Language: | English |
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2004
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| Online Access: | https://eprints.nottingham.ac.uk/10078/ |