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Cited by 112Probabilistic and Robust Engineering DesignRisk and Safety AnalysisGeotechnical Engineering and Analysis

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Sensitivity analysis in conjunction with evidence theory representations of epistemic uncertainty

Helton, J.C., Johnson, J.D., Oberkampf, W.L., Sallaberry, C.J.·2006·Reliability Engineering & System Safety
DOI 10.1016/j.ress.2005.11.055
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Crossref · 10.1016/j.ress.2005.11.055

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  • Probabilistic representations of uncertainty have been successfully employed with uniform distributions to characterise uncertainty when knowledge is sparse or absent.

    “Probabilistic representations of uncertainty have been successfully employed with uniform distributions to characterise uncertainty when knowledge is sparse or absent (Curto et al. 2022;Vanhoucke, 2018;Helton et al. 2006).”

    From Beyond probability-impact matrices in project risk management: A quantitative methodology for risk prioritisation (2024) · cites this paper as Helton et al. 2006

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Research works printed but not linked: 37

  1. Parry, 1981, Characterization and evaluation of uncertainty in probabilistic risk analysis, Nucl Saf, 22, 28
  2. Apostolakis, 1990, The concept of probability in safety assessments of technological systems, Science, 250, 1359, 10.1126/science.2255906 · DOI
  3. Helton, 1997, Uncertainty and sensitivity analysis in the presence of stochastic and subjective uncertainty, J Statist Comput Simul, 57, 3, 10.1080/00949659708811803 · DOI
  4. Turányi, 1990, Sensitivity analysis of complex kinetic systems. Tools and applications, J Math Chem, 5, 203, 10.1007/BF01166355 · DOI
  5. Cukier, 1978, Nonlinear sensitivity analysis of multiparameter model systems, J Comput Phys, 26, 1, 10.1016/0021-9991(78)90097-9 · DOI
  6. Sobol’, 1993, Sensitivity analysis for nonlinear mathematical models, Math Modeling Comput Exper, 1, 407
  7. Rabitz, 1999, Efficient input–output model representations, Comput Phys Commun, 117, 11, 10.1016/S0010-4655(98)00152-0 · DOI
  8. McKay, 1999, Evaluating prediction uncertainty in simulation models, Comput Phys Commun, 117, 44, 10.1016/S0010-4655(98)00155-6 · DOI
  9. Iman RL. Uncertainty and sensitivity analysis for computer modeling applications. In: Cruse TA, editor. Reliability technology—1992, the winter annual meeting of the American Society of Mechanical Engineers, Anaheim, CA, vol. 28. New York: American Society of Mechanical Engineers, Aerospace Division; November 8–13, 1992. p. 153–68.
  10. Kleijnen, 1999, Statistical analyses of scatterplots to identify important factors in large-scale simulations, 1: review and comparison of techniques, Reliab Eng Syst Saf, 65, 147, 10.1016/S0951-8320(98)00091-X · DOI
  11. Frey, 2002, Identification and review of sensitivity analysis methods, Risk Anal, 22, 553, 10.1111/0272-4332.00039 · DOI · Paper page
  12. Helton, 2002, Illustration of sampling-based methods for uncertainty and sensitivity analysis, Risk Anal, 22, 591, 10.1111/0272-4332.00041 · DOI
  13. Blower, 1994, Sensitivity and uncertainty analysis of complex models of disease transmission: an HIV model, as an example, Int Statist Rev, 62, 229, 10.2307/1403510 · DOI
  14. Hamby, 1994, A review of techniques for parameter sensitivity analysis of environmental models, Environ Monit Assess, 32, 135, 10.1007/BF00547132 · DOI
  15. Helton, 1993, Uncertainty and sensitivity analysis techniques for use in performance assessment for radioactive waste disposal, Reliab Eng Syst Saf, 42, 327, 10.1016/0951-8320(93)90097-I · DOI
  16. Klir, 1989, Is there more to uncertainty than some probability theorists might have us believe?, Int J Gen Syst, 15, 347, 10.1080/03081078908935057 · DOI
  17. Klir, 1994, On the alleged superiority of probability representation of uncertainty, IEEE Trans Fuzzy Syst, 2, 27, 10.1109/91.273119 · DOI
  18. Helton, 2004, An exploration of alternative approaches to the representation of uncertainty in model predictions, Reliab Eng Syst Saf, 85, 39, 10.1016/j.ress.2004.03.025 · DOI
  19. Kangas, 2004, Probability, possibility and evidence: approaches to consider risk and uncertainty in forestry decision analysis, For Policy Econ, 6, 169, 10.1016/S1389-9341(02)00083-7 · DOI
  20. Klir, 2004, Generalized information theory: aims, results, and open problems, Reliab Eng Syst Saf, 85, 21, 10.1016/j.ress.2004.03.003 · DOI
  21. Dempster, 1967, Upper and lower probabilities induced by a multivalued mapping, Ann Math Statist, 38, 325, 10.1214/aoms/1177698950 · DOI
  22. Wasserman, 1990, Belief functions and statistical inference, Can J Statist, 18, 183, 10.2307/3315449 · DOI
  23. Halpern, 1992, Two views of belief: belief as generalized probability and belief as evidence, Artif Intell, 54, 275, 10.1016/0004-3702(92)90048-3 · DOI
  24. Feller, 1971, vol. 2
  25. Helton, 2005, Competing failure risk analysis using evidence theory, Risk Anal, 25, 973, 10.1111/j.1539-6924.2005.00644.x · DOI
  26. Dempster, 1967, Upper and lower probability inferences based on a sample from a finite univariate population, Biometrika, 54, 515, 10.1093/biomet/54.3-4.515 · DOI
  27. Dempster, 1968, A generalization of Bayesian inference, J Roy Statist Soc Ser B, 30, 205, 10.1111/j.2517-6161.1968.tb00722.x · DOI
  28. McKay, 1979, A comparison of three methods for selecting values of input variables in the analysis of output from a computer code, Technometrics, 21, 239, 10.2307/1268522 · DOI
  29. Helton, 2003, Latin hypercube sampling and the propagation of uncertainty in analyses of complex systems, Reliab Eng Syst Saf, 81, 23, 10.1016/S0951-8320(03)00058-9 · DOI
  30. Iman, 1979, The use of the rank transform in regression, Technometrics, 21, 499, 10.2307/1268289 · DOI
  31. Hora, 2003, A distribution-free test for the relationship between model input and output when using Latin hypercube sampling, Reliab Eng Syst Saf, 79, 333, 10.1016/S0951-8320(02)00240-5 · DOI
  32. Iman, 1980, Small sample sensitivity analysis techniques for computer models, with an application to risk assessment, Commun Statist Theory Methods, A9, 1749, 10.1080/03610928008827996 · DOI
  33. Beckman, 1987, Monte-Carlo estimation under different distributions using the same simulation, Technometrics, 29, 153, 10.2307/1269770 · DOI
  34. Helton, 2006, Probability of loss of assured safety in temperature dependent systems with multiple weak and strong links, Reliab Eng Syst Saf, 91, 320, 10.1016/j.ress.2005.01.011 · DOI
  35. Seal, 1977, Studies in the history of probability and statistics, XXXV, Multiple decrements or competing risks. Biometrika, 64, 429
  36. Gail, 1975, Review and critique of some models used in competing risk analysis, Biometrics, 31, 209, 10.2307/2529721 · DOI
  37. Hora, 1989, Expert opinion in risk analysis: the NUREG-1150 methodology, Nucl Sci Eng, 102, 323, 10.13182/NSE89-A23645 · DOI

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Metadata

Authors
Helton, J. C., Johnson, J. D., Oberkampf, W. L., & Sallaberry, C. J.
Affiliations
  • Arizona State University (US)
  • Sandia National Laboratories (US)
Corresponding author
Helton, J.C.
ORCID
Johnson, J.D.
Venue
Reliability Engineering & System Safety
Publisher
Elsevier BV
Published
2006-10
Volume
91
Issue
10-11
Pages
1414-1434
ISSN
0951-8320 (ISSN-L)
DOI
10.1016/j.ress.2005.11.055
OpenAlex
W1991853987
Cited by
112
References
1
Citations by year
2026: 2 · 2024: 5 · 2023: 2 · 2022: 3 · 2021: 10 · 2020: 7 · 2019: 6 · 2018: 10 · 2017: 3 · 2016: 4 · 2015: 6 · 2014: 10 · 2013: 8 · 2012: 8
FWCI
6.85
Type
journal article
Language
en
Open access
closed
Licence
www.elsevier.com/tdm/userlicense/1.0/ (tdm)
Locations
  • Reliability Engineering & System Safety (publishedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
Funders
  • U.S. Department of Energy
  • Children's Cancer and Blood Foundation
  • California Consumer Protection Foundation
  • Sandia National Laboratories
Topics
  • Physical Sciences › Engineering › Computational Mechanics › Probabilistic and Robust Engineering Design
  • Physical Sciences › Engineering › Safety, Risk, Reliability and Quality › Risk and Safety Analysis
  • Physical Sciences › Engineering › Civil and Structural Engineering › Geotechnical Engineering and Analysis
Keywords
sensitivity analysis, Dempster-Shafer theory, epistemic uncertainty, model input data, belief functions, plausibility function, cumulative distribution function, variance-based sensitivity analysis, probability-possibility transformation, error propagation

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