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The Bayes linear approach to inference and decision-making for a reliability programme

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  • Goldstein, Michael
  • Bedford, Tim

Abstract

In reliability modelling it is conventional to build sophisticated models of the probabilistic behaviour of the component lifetimes in a system in order to deduce information about the probabilistic behaviour of the system lifetime. Decision modelling of the reliability programme requires a priori, therefore, an even more sophisticated set of models in order to capture the evidence the decision maker believes may be obtained from different types of data acquisition.

Suggested Citation

  • Goldstein, Michael & Bedford, Tim, 2007. "The Bayes linear approach to inference and decision-making for a reliability programme," Reliability Engineering and System Safety, Elsevier, vol. 92(10), pages 1344-1352.
    • Handle: RePEc:eee:reensy:v:92:y:2007:i:10:p:1344-1352
    DOI: 10.1016/j.ress.2006.09.010
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    References listed on IDEAS

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    1. Michael Goldstein, 2004. "Bayes linear kinematics and Bayes linear Bayes graphical models," Biometrika, Biometrika Trust, vol. 91(2), pages 425-446, June.
    2. Craig P. S & Goldstein M. & Rougier J. C & Seheult A. H, 2001. "Bayesian Forecasting for Complex Systems Using Computer Simulators," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 717-729, June.
    3. A. O'Hagan & E. B. Glennie & R. E. Beardsall, 1992. "Subjective Modelling and Bayes Linear Estimation in the Uk Water Industry," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 41(3), pages 563-577, November.
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    Cited by:

    1. John Quigley & Kevin J. Wilson & Lesley Walls & Tim Bedford, 2013. "A Bayes Linear Bayes Method for Estimation of Correlated Event Rates," Risk Analysis, John Wiley & Sons, vol. 33(12), pages 2209-2224, December.

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