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 (Unpublished)

Full text not available in this repository.Request a copy


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.


Wilson, Kevin, Quigley, John, Bedford, Tim ORCID logoORCID: and Walls, Lesley ORCID logoORCID:;