Statistical Science

Bayesian Nonparametrics for Stochastic Epidemic Models

Theodore Kypraios and Philip D. O’Neill

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The vast majority of models for the spread of communicable diseases are parametric in nature and involve underlying assumptions about how the disease spreads through a population. In this article, we consider the use of Bayesian nonparametric approaches to analysing data from disease outbreaks. Specifically we focus on methods for estimating the infection process in simple models under the assumption that this process has an explicit time-dependence.

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Statist. Sci., Volume 33, Number 1 (2018), 44-56.

First available in Project Euclid: 2 February 2018

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Bayesian nonparametrics epidemic model Gaussian process


Kypraios, Theodore; O’Neill, Philip D. Bayesian Nonparametrics for Stochastic Epidemic Models. Statist. Sci. 33 (2018), no. 1, 44--56. doi:10.1214/17-STS617.

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