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Probabilistic Safety Assessment and Management pp 2784–2790Cite as

Non-Parametric Continuous Bayesian Belief Nets with Expert Judgement

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Abstract

This report introduces continuous belief nets using the vine — copulae modelling approach. Nodes are associated with continuous distributions, influences are associated with (conditional) rank correlations and are realized by (conditional) copulae. Any copula which represents (conditional) independence as zero (conditional) correlation can be used. We present an elicitation protocol based on (conditional) rank correlations and show how a unique joint distribution preserving the conditional independence properties of the Bayesian belief net can be determined, sampled and updated.

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References

  1. Bedford T.J. and Cooke R.M.. Vines — a new graphical model for dependent random variables. Ann. Stat. 2002; 30 no 4: 1031–1068.

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  2. Kurowicka D. and Cooke R.M. The vine copula method for representing high dimensional dependent distributions; application to continuous belief nets. Proc. Winter Simulation Conference. Yucesan et al (eds) 2002.

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  4. Cooke R.M. Markov and entropy properties of tree and vines-dependent variables, Proc. of the ASA Section of Bayesian Statistical Science. 1997.

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Author information

Authors and Affiliations

  1. Delft Institute of Applied Mathematics, Delft University of Technology, Delft, The Netherlands

    Dorota Kurowicka & Roger Cooke

Authors
  1. Dorota Kurowicka
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  2. Roger Cooke
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Editor information

Editors and Affiliations

  1. TÜV Süddeutschland, Dudenstrasse 28, D-68167, Mannheim, Germany

    Cornelia Spitzer Dipl.-Math.

  2. Swiss Federal Nuclear Safety Inspectorate (HSK), CH-5232, Villigen-HSK, Switzerland

    Ulrich Schmocker PhD

  3. Paul Scherrer Institut (PSI), CH-5232, Villigen PSI, Switzerland

    Vinh N. Dang PhD

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© 2004 Springer-Verlag London

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Cite this paper

Kurowicka, D., Cooke, R. (2004). Non-Parametric Continuous Bayesian Belief Nets with Expert Judgement. In: Spitzer, C., Schmocker, U., Dang, V.N. (eds) Probabilistic Safety Assessment and Management. Springer, London. https://doi.org/10.1007/978-0-85729-410-4_446

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  • DOI: https://doi.org/10.1007/978-0-85729-410-4_446

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-4471-1057-6

  • Online ISBN: 978-0-85729-410-4

  • eBook Packages: Springer Book Archive

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