University of Edinburgh
School of Mathematics and BioSS
Date: Friday 3rd March, 15:10 Location: JCMB 6201
Speaker: Theodore Kypraios, University of Nottingham
Title: Recent Developments in Bayesian Non-Parametric Inference for Epidemic Models
Abstract: Despite the enormous attention given to the development of methods for
efficient parameter estimation, there has been relatively little
activity in the area of non- parametric inference. That is, drawing
inference for the quantities which govern transmission, i) the force of
infection and ii) the period during which an individual remains
infectious, without making certain modelling assumptions about its
(parametric) functional form or that it belongs to a certain family of
parametric distributions.
In this talk I will describe a number of approaches which allow Bayesian
non-parametric inference for the force of infection; namely via Gaussian
Processes, Step Functions, and B-splines. I will also illustrate the
proposed methodology via both simulated and real datasets and discuss
how such methods can scale for large populations.
This seminar is a part of Maxwell Institute seminar series.
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