A Review of Modern Computational Algorithms for Bayesian Optimal Design

Bayesian experimental design is a fast growing area of research with many real-world applications. As computational power has increased over the years, so has the development of simulation-based design methods, which involve a number of algorithms, such as Markov chain Monte Carlo, sequential Monte...

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Bibliographic Details
Published in:	International statistical review Vol. 84; no. 1; pp. 128 - 154
Main Authors:	Ryan, Elizabeth G., Drovandi, Christopher C., McGree, James M., Pettitt, Anthony N.
Format:	Journal Article
Language:	English
Published:	Hoboken Blackwell Publishing Ltd 01.04.2016 Blackwell Publishing John Wiley & Sons, Inc
Subjects:	Algorithms Bayesian analysis Bayesian optimal design Computation Computer simulation decision theory Experiments Mathematical analysis Mathematical models Monte Carlo simulation Optimization posterior distribution approximation Simulation stochastic optimisation Utilities utility function
ISSN:	0306-7734, 1751-5823
Online Access:	Get full text
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