Bayesian Inference for Stochastic Epidemic Models using Markov chain Monte Carlo Methods

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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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Bibliographic Details
Main Author:	Demiris, Nikolaos
Format:	Thesis (University of Nottingham only)
Language:	English
Published:	2004
Subjects:	Bayesian Inference Stochastic Epidemic Models Markov chain Monte Carlo Methods
Online Access:	https://eprints.nottingham.ac.uk/10078/

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