Statistics and Computing

, Volume 13, Issue 1, pp 37–44 | Cite as

Perfect simulation for Reed-Frost epidemic models

  • Philip D. O'Neill
Article

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.

epidemics stochastic epidemic models Reed-Frost epidemic model perfect simulation Markov chain Monte Carlo methods Bayesian inference 

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Copyright information

© Kluwer Academic Publishers 2003

Authors and Affiliations

  • Philip D. O'Neill
    • 1
  1. 1.School of Mathematical SciencesUniversity of NottinghamNottinghamEngland

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