Abstract
The problem of using expert estimates is investigated. These estimates are treated as evidence that must be evaluated by a decision maker and incorporated into his body of knowledge and beliefs. This is done coherently using Bayes’ theorem. Two models are proposed based on normal and lognormal likelihood functions, which represent the decision maker’s model of the credibility of the expert estimates. Several commonly used methods, e. g., taking the geometric average of the expert estimates, are investigated in the context of the general methods of this paper.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
U.S. Nuclear Regulatory Commission, Reactor Safety Study, WASH-1400, NUREG-75/014 (October 1975).
Institute of Electrical and Electronics Engineers, IEEE Guide to the Collection and Presentation of Electrical, Electronic, and Sensing Component Reliability Data for Nuclear-Power Generating Stations, IEEE Std-500 (1977).
R. L. Winkler, The Consensus of Subjective Probability Distributions, Management Science, 15, 61 (1968).
J. P. Dickinson, Some Statistical Results in the Combination of Forecasts, Operational Research Quarterly, 24, 253 (1973).
J. P. Dickinson, Some Comments on the Combination of Forecasts, Operational Research Quarterly, 26, 205 (1975).
H. F. Martz and R. A. Waller, An Exploratory Comparison of Methods for Combining Failure-Rate Data from Different Data Sources, Los Alamos National Laboratory, LA-7556-MS (1978).
B. De Finetti, Theory of Probability, Vols 1 and 2, John Wiley and Sons, New York (1974).
G. Apostolakis, Bayesian Methods in Risk Assessment, in: Advances in Nuclear Science and Technology (J. Lewins and M. Becker, eds.), 13, 415, Plenum Press, New York (1981).
S. Kaplan and B. J. Garrick, On the Quantitative Definition of Risk, Risk Analysis, 1, 11 (1981).
S. Kaplan, G. Apostolakis, B. J. Garrick, D. C. Bley, and K. Woodard, Methodology for Probabilistic Risk Assessment of Nuclear Power Plants, Report PLG-0209, Pickard, Lowe, and Garrick, Inc., Irvine, California (1981).
G. W. Parry and P. W. Winter, Characterization and Evaluation of Uncertainty in Probabilistic Risk Analysis, Nuclear Safety, 22, 28 (1981).
R. G. Easterling, Bayesianism, Letter to the Editor, Nuclear Safety, 22, 464 (1981).
D. V. Lindley, Making Decisions, Wiley, New York (1971).
A. W. Blackman, Jr., The Use of Bayesian Techniques in Delphi Forecasts, Technological Forecasting and Social Change, 2, 261 (1971).
P. A. Morris, Decision Analysis Experts Use, Management Science, 20, 1233 (1974).
G. Apostolakis and A. Mosleh, Expert Opinion and Statistical Evidence: An Application to Reactor Core Melt Frequency, Nuclear Science and Engineering, 70, 135 (1979).
H. F. Martz, On the Correct Use of the Bayesian Method for Reactor Core Melt Frequency, Letter to the Editor, Nuclear Science and Engineering, 72, 368 (1979).
R. G. Easterling, Comments on the Bayesian Method for Estimating Reactor Core Melt Frequency, Letter to the Editor, Nuclear Science and Engineering, 75, 202 (1980).
D. V. Lindley, Introduction to Probability and Statistics, Part 1: Probability, Part 2: Inference, Cambridge University Press (1970).
N. C. Dalkey, An Experimental Study of Group Opinion, RM-5888-PR, The RAND Corporation, Santa Monica, California (1969).
J. P. Martino, Lognormality of Delphi Estimates, Technological Forecasting, 1, 355 (1970).
S. J. Press, Applied Multivariate Analysis, Holt, Rinehard, and Winston (1973).
After this paper was completed it came to our attention that some of the results for the case of additive errors were reported in: R. L. Winkler, Combining Probability Distributions from Dependent Information Sources, Management Science, 27, 479 (1981).
N. Dalkey, B. Brown, and S. Cochran, Use of Self-Ratings to Improve Group Estimates, Technological Forecasting, 1, 283 (1970).
S. Lichtenstein, B. Fischhoff, and L. D. Phillips, Calibration of Probabilities: The State of the Art, in: Decision Making and Change in Human Affairs (J. Jungermann and G. de Zeeuw, eds.), D. Reidel Publishing Co., Dordrecht, Holland (1977).
G. B. Baecher, Correlations Among Experts’ Opinions, Unpublished Manuscript, Department of Civil Engineering, Massachusetts Institute of Technology (1979).
G. Apostolakis, S. Kaplan, B. J. Garrick, and R. J. Duphily, Data Specialization for Plant-Specific Risk Studies, Nuclear Engineering and Design, 56, 321 (1980).
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 1984 Springer Science+Business Media New York
About this chapter
Cite this chapter
Mosleh, A., Apostolakis, G. (1984). Models for the use of Expert Opinions. In: Waller, R.A., Covello, V.T. (eds) Low-Probability High-Consequence Risk Analysis. Advances in Risk Analysis, vol 2. Springer, Boston, MA. https://doi.org/10.1007/978-1-4757-1818-8_7
Download citation
DOI: https://doi.org/10.1007/978-1-4757-1818-8_7
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4757-1820-1
Online ISBN: 978-1-4757-1818-8
eBook Packages: Springer Book Archive