Fiducial inference in combining expert judgements

Paola Monari () and Patrizia Agati
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Paola Monari: University of Bologna

Statistical Methods & Applications, 2001, vol. 10, issue 1, No 8, 97 pages

Abstract: 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.

Keywords: Fiducial inference; expert judgement; hierarchical Bayes; calibration function (search for similar items in EconPapers)
Date: 2001
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DOI: 10.1007/BF02511641

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