Perfect simulation for Reed-Frost epidemic models |
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Authors: | Philip D O'Neill |
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Institution: | (1) School of Mathematical Sciences, University of Nottingham, University Park, Nottingham, NG7 2RD, England |
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Abstract: | The Reed-Frost epidemic model is a simple stochastic process with parameter q that describes the spread of an infectious disease among a closed population. Given data on the final outcome of an epidemic, it is possible to perform Bayesian inference for q using a simple Gibbs sampler algorithm. In this paper it is illustrated that by choosing latent variables appropriately, certain monotonicity properties hold which facilitate the use of a perfect simulation algorithm. The methods are applied to real data. |
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Keywords: | epidemics stochastic epidemic models Reed-Frost epidemic model perfect simulation Markov chain Monte Carlo methods Bayesian inference |
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