Statistical Methods and Applications

, Volume 10, Issue 1–3, pp 81–97 | Cite as

Fiducial inference in combining expert judgements

  • Paola Monari
  • Patrizia Agati
Statistical Methods
  • 67 Downloads

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.

Key words

Fiducial inference expert judgement hierarchical Bayes calibration function 

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Copyright information

© Springer-Verlag 2001

Authors and Affiliations

  • Paola Monari
    • 1
  • Patrizia Agati
    • 1
  1. 1.Dept. of Sciencze StatisticheUniversity of BolognaBolognaItaly

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