Bayes linear graphical models in the design of optimal test strategies

Research output: Contribution to conferencePaper


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.
Original languageEnglish
Publication statusUnpublished - Jul 2013
Event8th International Conference on Mathematical Methods in Reliability (MMR2013) - Stellenboch, South Africa
Duration: 1 Jul 20134 Jul 2013


Conference8th International Conference on Mathematical Methods in Reliability (MMR2013)
Country/TerritorySouth Africa


  • Bayesian modelling
  • Bayes graphical model
  • Bayesian belief networks

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