Bayes linear graphical models in the design of optimal test strategies
Wilson, Kevin and Quigley, John and Bedford, Tim and Walls, Lesley (2013) Bayes linear graphical models in the design of optimal test strategies. In: 8th International Conference on Mathematical Methods in Reliability (MMR2013), 2013-07-01 - 2013-07-04. (Unpublished)
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Testing plays a vital role in reducing uncertainty but is resource intensive and identifying the best design is a difficult process. During the development of a system there are a number of potential tests that can be performed with varying efficacy and resource requirements. In this paper we propose a Bayesian modelling process which takes the form of a Bayesian Belief Network (BBN) to determine test efficacy and permits programme managers to assess optimal trade-offs between uncertainty reduction and resources. Supporting inference from a full Bayesian model can be prohibitively expensive computationally so we utilise a Bayes linear approximation, known as a Bayes linear Bayes graphical model, to the inference.
ORCID iDs
Wilson, Kevin, Quigley, John, Bedford, Tim

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Item type: Conference or Workshop Item(Paper) ID code: 45772 Dates: DateEventJuly 2013PublishedKeywords: Bayesian modelling, Bayes graphical model, Bayesian belief networks, Management. Industrial Management, Management Science and Operations Research Subjects: Social Sciences > Industries. Land use. Labor > Management. Industrial Management Department: Strathclyde Business School > Management Science Depositing user: Pure Administrator Date deposited: 08 Nov 2013 11:57 Last modified: 18 Jan 2023 13:12 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/45772