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Identifying the Infectious Period Distribution for Stochastic Epidemic Models Using the Posterior Predictive Check
Conference proceeding

Identifying the Infectious Period Distribution for Stochastic Epidemic Models Using the Posterior Predictive Check

Muteb Alharthi, Philip O'Neill and Theodore Kypraios
BAYESIAN STATISTICS FROM METHODS TO MODELS AND APPLICATIONS: RESEARCH FROM BAYSM 2014, Vol.126, pp.109-114
Springer Proceedings in Mathematics & Statistics
01/01/2015
DOI: https://doi.org/10.1007/978-3-319-16238-6_9

Abstract

Mathematics Physical Sciences Science & Technology Statistics & Probability
Under the Bayesian framework, we develop a novel method for assessing the goodness of fit for the SIR (susceptible-infective-removed) stochastic epidemic model. This method seeks to determine whether or not one can identify the infectious period distribution based only on a set of partially observed data using a posterior predictive distribution approach. Our criterion for assessing the model's goodness of fit is based on the notion of Bayesian residuals.

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