Accession Number:

ADP005295

Title:

A Bayesian View of Assessing Uncertainty and Comparing Expert Opinion

Descriptive Note:

Technical rept.

Corporate Author:

CARNEGIE-MELLON UNIV PITTSBURGH PA DEPT OF STATISTICS

Personal Author(s):

Report Date:

1987-03-16

Pagination or Media Count:

25.0

Abstract:

A Bayesian approach to the problem of comparing experts or expert systems is presented. The question of who is an expert is considered and comparisons among well-calibrated experts are studied. The concept of refinement, in various equivalent forms, is used in this study. An informative example of the combination of the opinions of well-calibrated experts is described. Total orderings of the class of well-calibrated experts are derived from strictly proper scoring rules. Keywords predictions Forecasters Well calibrated Expert systems Combining opinion Scoring rules.

Subject Categories:

  • Statistics and Probability

Distribution Statement:

APPROVED FOR PUBLIC RELEASE