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Fiducial inference in combining expert judgements

Author

Listed:
  • Paola Monari

    (University of Bologna)

  • Patrizia Agati

    (University of Bologna)

Abstract

In the expert use problem, hierarchical models provide an ideal perspective for classifying understanding and generalising the aggregative algoithms suitable to compose experts' opinions in a single synthesis distribution. After suggesting to look at Peter A. Morris' (1971, 1974, 1977) Bayesian model in such a light, this paper addresses the problem of modelling the multidimensional ‘performance function’, which encodes aggregator's beliefs about each expert's assessment ability and the degree of dependence among the experts. Whenever the aggregator has not an empirically founded probability distribution for the experts' performances, the proposed fiducial procedure provides a rational and very flexible tool for enabling the performance function to be specified with a relatively small number of assessments: moreover, it warrants aggregator's beliefs about the experts in terms of personal long run frequencies.

Suggested Citation

  • Paola Monari & Patrizia Agati, 2001. "Fiducial inference in combining expert judgements," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 10(1), pages 81-97, January.
    • Handle: RePEc:spr:stmapp:v:10:y:2001:i:1:d:10.1007_bf02511641
    DOI: 10.1007/BF02511641
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    References listed on IDEAS

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