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Activity Number: 573 - Design of Experiments for Stochastic Process Models
Type: Topic Contributed
Date/Time: Wednesday, August 1, 2018 : 2:00 PM to 3:50 PM
Sponsor: Royal Statistical Society
Abstract #329282 Presentation
Title: Efficient Construction of Bayes Optimal Designs for Stochastic Process Models
Author(s): Richard Boys*
Companies: Newcastle University
Keywords: sequential; particle; parallel computing

Recent advances in the construction of Bayes optimal experimental designs for stochastic process models have been limited due to them being computationally intensive, even for relatively simple models. However progress can be made by using a sequential particle-based approach in which the algorithm increasingly focuses on a region around the optimal design. In this talk we describe the algorithm, investigate its computational performance against other competitive algorithms and illustrate the results with examples.

Authors who are presenting talks have a * after their name.

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