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Customized Structural Elicitation

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Expert Judgement in Risk and Decision Analysis

Part of the book series: International Series in Operations Research & Management Science ((ISOR,volume 293))

Abstract

Expert elicitation is a powerful tool when modelling complex problems, especially in the common scenario when current probabilities are unknown and data is unavailable for certain regions of the probability space. Such methods are now widely developed, well understood, and have been used to model systems in a variety of domains including climate change, food insecurity, and nuclear risk assessment Barons et al. (2018), Rougier and Crucifix (2018), Hanea et al. (2006). However, eliciting expert probabilities faithfully has proved to be a sensitive task, particularly in multivariate settings. We argue that first eliciting structure is critical to the accuracy of the model, particularly as conducting a probability elicitation is time and resource-intensive.

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Acknowledgements

The authors would like to thank The Alan Turing Institute EPSRC Grant EP/L016710/1 and the Leverhulme Bridges for their support.

Author information

Authors and Affiliations

  1. University of Warwick, Warwick, UK

    Rachel L. Wilkerson

  2. Alan Turing Institute, University of Warwick, Warwick, UK

    Jim Q. Smith

Authors
  1. Rachel L. Wilkerson
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  2. Jim Q. Smith
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Corresponding author

Correspondence to Rachel L. Wilkerson .

Editor information

Editors and Affiliations

  1. Center of Excellence for Biosecurity Risk Analysis (CEBRA), University of Melbourne, Melbourne, VIC, Australia

    Anca M. Hanea

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

    Gabriela F. Nane

  3. Department of Management Science, University of Strathclyde, Glasgow, UK

    Tim Bedford

  4. Department of Statistics, University of Warwick, Coventry, UK

    Simon French

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Wilkerson, R.L., Smith, J.Q. (2021). Customized Structural Elicitation. In: Hanea, A.M., Nane, G.F., Bedford, T., French, S. (eds) Expert Judgement in Risk and Decision Analysis. International Series in Operations Research & Management Science, vol 293. Springer, Cham. https://doi.org/10.1007/978-3-030-46474-5_4

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