Bayesian nonparametric methods for individual-level stochastic epidemic models

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Bayesian nonparametric methods for individual-level stochastic epidemic models

Simulating from and making inference for stochastic epidemic models are key strategies for understanding and controlling the spread of infectious diseases. Current methods for modelling infection rate functions are exclusively parametric. This often involves making strict assumptions about the way t...

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Bibliographic Details
Main Author:	Seymour, Rowland G.
Format:	Thesis (University of Nottingham only)
Language:	English
Published:	2020
Subjects:	Bayesian Nonparametrics Bayesian Computation Epidemic Modelling
Online Access:	https://eprints.nottingham.ac.uk/60671/

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