Combining Probability Distributions From Experts in Risk Analysis

Combining Probability Distributions From Experts in Risk Analysis This paper concerns the combination of experts' probability distributions in risk analysis, discussing a variety of combination methods and attempting to highlight the important conceptual and practical issues to be considered in designing a combination process in practice. The role of experts is important because their judgments can provide valuable information, particularly in view of the limited availability of “hard data” regarding many important uncertainties in risk analysis. Because uncertainties are represented in terms of probability distributions in probabilistic risk analysis (PRA), we consider expert information in terms of probability distributions. The motivation for the use of multiple experts is simply the desire to obtain as much information as possible. Combining experts' probability distributions summarizes the accumulated information for risk analysts and decision‐makers. Procedures for combining probability distributions are often compartmentalized as mathematical aggregation methods or behavioral approaches, and we discuss both categories. However, an overall aggregation process could involve both mathematical and behavioral aspects, and no single process is best in all circumstances. An understanding of the pros and cons of different methods and the key issues to consider is valuable in the design of acombination process for a specific PRA. The output, a ”combined probabilitydistribution,” can ideally be viewed as representing a summary of the current state of expert opinion regarding the uncertainty of interest. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Risk Analysis Wiley

Combining Probability Distributions From Experts in Risk Analysis

Risk Analysis, Volume 19 (2) – Apr 1, 1999

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Publisher
Wiley
Copyright
Copyright © 1999 Wiley Subscription Services, Inc., A Wiley Company
ISSN
0272-4332
eISSN
1539-6924
DOI
10.1111/j.1539-6924.1999.tb00399.x
Publisher site
See Article on Publisher Site

Abstract

This paper concerns the combination of experts' probability distributions in risk analysis, discussing a variety of combination methods and attempting to highlight the important conceptual and practical issues to be considered in designing a combination process in practice. The role of experts is important because their judgments can provide valuable information, particularly in view of the limited availability of “hard data” regarding many important uncertainties in risk analysis. Because uncertainties are represented in terms of probability distributions in probabilistic risk analysis (PRA), we consider expert information in terms of probability distributions. The motivation for the use of multiple experts is simply the desire to obtain as much information as possible. Combining experts' probability distributions summarizes the accumulated information for risk analysts and decision‐makers. Procedures for combining probability distributions are often compartmentalized as mathematical aggregation methods or behavioral approaches, and we discuss both categories. However, an overall aggregation process could involve both mathematical and behavioral aspects, and no single process is best in all circumstances. An understanding of the pros and cons of different methods and the key issues to consider is valuable in the design of acombination process for a specific PRA. The output, a ”combined probabilitydistribution,” can ideally be viewed as representing a summary of the current state of expert opinion regarding the uncertainty of interest.

Journal

Risk AnalysisWiley

Published: Apr 1, 1999

References

  • Testing for unreliable estimators and insignificant forecasts in combined forecasts
    Chandrasekharan, Chandrasekharan; Moriarty, Moriarty; Wright, Wright
  • Extraneous expert information
    Clemen, Clemen
  • Pooling operators with the marginalization property
    Genest, Genest
  • Allocating the weights in the linear opinion pool
    Genest, Genest; McConway, McConway
  • The expected value of information and the probability of surprise
    Hammitt, Hammitt; SNyakhter, SNyakhter
  • The use of decomposition in probability assessments on continuous variables
    Hora, Hora; Dodd, Dodd; Hora, Hora
  • Expert judgment in risk analysis and management: Process, context, and pitfalls
    Otway, Otway; Winterfeldt, Winterfeldt
  • A review of research on groupthink
    Park, Park
  • Improved framework for uncertainty analysis: Accounting for unsuspected errors
    Shlyakhter, Shlyakhter
  • The combination of forecasts
    Winkler, Winkler; Makridakis, Makridakis

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