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Methods for Uncertainty Analysis: A Comparative Survey

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  • David C. Cox
  • Paul Baybutt

Abstract

This paper presents a survey and comparative evaluation of methods which have been developed for the determination of uncertainties in accident consequences and probabilities, for use in probabilistic risk assessment. The methods considered are: analytic techniques, Monte Carlo simulation, response surface approaches, differential sensitivity techniques, and evaluation of classical statistical confidence bounds. It is concluded that only the response surface and differential sensitivity approaches are sufficiently general and flexible for use as overall methods of uncertainty analysis in probabilistic risk assessment. The other methods considered, however, are very useful in particular problems.

Suggested Citation

  • David C. Cox & Paul Baybutt, 1981. "Methods for Uncertainty Analysis: A Comparative Survey," Risk Analysis, John Wiley & Sons, vol. 1(4), pages 251-258, December.
    • Handle: RePEc:wly:riskan:v:1:y:1981:i:4:p:251-258
    DOI: 10.1111/j.1539-6924.1981.tb01425.x
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    Cited by:

    1. Fritz A. Seiler, 1987. "Error Propagation for Large Errors," Risk Analysis, John Wiley & Sons, vol. 7(4), pages 509-518, December.
    2. Anand Patwardhan & Mitchell J. Small, 1992. "Bayesian Methods for Model Uncertainty Analysis with Application to Future Sea Level Rise," Risk Analysis, John Wiley & Sons, vol. 12(4), pages 513-523, December.
    3. James K. Hammitt, 1990. "Subjective‐Probability‐Based Scenarios for Uncertain Input Parameters: Stratospheric Ozone Depletion," Risk Analysis, John Wiley & Sons, vol. 10(1), pages 93-102, March.
    4. Gradov, Dmitry Vladimirovich & Yusuf, Yusuf Oluwatoki & Ohjainen, Jussi & Suuronen, Jarkko & Eskola, Roope & Roininen, Lassi & Koiranen, Tuomas, 2022. "Modelling of a continuous veneer drying unit of industrial scale and model-based ANOVA of the energy efficiency," Energy, Elsevier, vol. 244(PA).
    5. Brent Finley & Dennis Paustenbach, 1994. "The Benefits of Probabilistic Exposure Assessment: Three Case Studies Involving Contaminated Air, Water, and Soil," Risk Analysis, John Wiley & Sons, vol. 14(1), pages 53-73, February.
    6. John H. Miller, 1998. "Active Nonlinear Tests (ANTs) of Complex Simulation Models," Management Science, INFORMS, vol. 44(6), pages 820-830, June.
    7. Max Henrion & M. Granger Morgan, 1985. "A Computer Aid for Risk and Other Policy Analysis," Risk Analysis, John Wiley & Sons, vol. 5(3), pages 195-208, September.
    8. Yan, Weichao & Meng, Xiangzhao & Cui, Xin & Liu, Yilin & Chen, Qian & Jin, Liwen, 2022. "Evaporative cooling performance prediction and multi-objective optimization for hollow fiber membrane module using response surface methodology," Applied Energy, Elsevier, vol. 325(C).
    9. John H. Miller, 1996. "Active Nonlinear Tests (ANTs) of Complex Simulation Models," Working Papers 96-03-011, Santa Fe Institute.
    10. Andrew E. Smith & P. Barry Ryan & John S. Evans, 1992. "The Effect of Neglecting Correlations When Propagating Uncertainty and Estimating the Population Distribution of Risk," Risk Analysis, John Wiley & Sons, vol. 12(4), pages 467-474, December.
    11. Fritz A. Seiler & Joseph L. Alvarez, 1996. "On the Selection of Distributions for Stochastic Variables," Risk Analysis, John Wiley & Sons, vol. 16(1), pages 5-18, February.
    12. El-Awady, Ahmed & Ponnambalam, Kumaraswamy, 2021. "Integration of simulation and Markov Chains to support Bayesian Networks for probabilistic failure analysis of complex systems," Reliability Engineering and System Safety, Elsevier, vol. 211(C).
    13. Vincent T. Covello, 1987. "Decision Analysis and Risk Management Decision Making: Issues and Methods," Risk Analysis, John Wiley & Sons, vol. 7(2), pages 131-139, June.

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