Contributions to Bayesian experimental design

Ryan, Elizabeth G. (2014) Contributions to Bayesian experimental design. PhD by Publication, Queensland University of Technology.


This thesis progresses Bayesian experimental design by developing novel methodologies and extensions to existing algorithms. Through these advancements, this thesis provides solutions to several important and complex experimental design problems, many of which have applications in biology and medicine. This thesis consists of a series of published and submitted papers. In the first paper, we provide a comprehensive literature review on Bayesian design. In the second paper, we discuss methods which may be used to solve design problems in which one is interested in finding a large number of (near) optimal design points. The third paper presents methods for finding fully Bayesian experimental designs for nonlinear mixed effects models, and the fourth paper investigates methods to rapidly approximate the posterior distribution for use in Bayesian utility functions.

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236 since deposited on 17 Feb 2015
123 in the past twelve months

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ID Code: 79628
Item Type: QUT Thesis (PhD by Publication)
Supervisor: Pettitt, Tony, Drovandi, Christopher, & Thompson, Helen
Keywords: Bayesian optimal design, Decision theory, Utility function, Stochastic optimisation, Markov chain Monte Carlo, Posterior distribution approximation, Sampling strategies, Pharmacokinetics
Divisions: Current > Schools > School of Mathematical Sciences
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Institution: Queensland University of Technology
Deposited On: 17 Feb 2015 05:33
Last Modified: 08 Sep 2015 06:45

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