Skip to main content

Research Repository

Advanced Search

Bayesian nonparametrics for stochastic epidemic models

Kypraios, Theodore; O'Neill, Philip D.


Professor of Applied Probability


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.


Kypraios, T., & O'Neill, P. D. (2018). Bayesian nonparametrics for stochastic epidemic models. Statistical Science, 33(1),

Journal Article Type Article
Acceptance Date Jun 3, 2017
Publication Date Feb 2, 2018
Deposit Date Jun 9, 2017
Publicly Available Date Feb 2, 2018
Journal Statistical Science
Print ISSN 0883-4237
Electronic ISSN 2168-8745
Publisher Institute of Mathematical Statistics (IMS)
Peer Reviewed Peer Reviewed
Volume 33
Issue 1
Keywords Bayesian nonparametrics, Epidemic model, Gaussian process
Public URL
Publisher URL

Files (314 Kb)

Copyright Statement
Copyright information regarding this work can be found at the following address:

You might also like

Downloadable Citations