Representation, propagation, and decision issues in risk analysis under incomplete probabilistic information: Commentary

Risk Analysis

Volumn 30, Issue 3, 2010, Pages 361-368

  Dubois, Didier ^a  

^a IRIT   (France)

Author keywords

[No Author keywords available]

Indexed keywords

BOUNDING ANALYSIS; EXPERT JUDGMENT; IMPRECISE PROBABILITIES; INCOMPLETE INFORMATION; POSSIBILITY THEORY; PROBABILISTIC APPROACHES; PROBABILISTIC INFORMATION; RANDOM SET; UNCERTAINTY THEORY;

DECISION MAKING; RISK ANALYSIS; RISK ASSESSMENT; SAFETY FACTOR; SET THEORY; UNCERTAINTY ANALYSIS;

PROBABILITY DISTRIBUTIONS;

DECISION MAKING; PRECISION; PROBABILITY; RISK ASSESSMENT; THEORETICAL STUDY;

DECISION MAKING; HUMAN; PROBABILITY; REVIEW; RISK; RISK ASSESSMENT; UNCERTAINTY;

HUMANS; JUDGMENT; PROBABILITY; RISK; RISK ASSESSMENT; UNCERTAINTY;

EID: 77949399403     PISSN: 02724332     EISSN: 15396924     Source Type: Journal    
DOI: 10.1111/j.1539-6924.2010.01359.x     Document Type: Review

References (33)

1. Aven T. On the need for restricting the probabilistic analysis in risk assessments to variability. Risk Analysis, to appear, 2010.
2. Ferson S, Ginzburg LR. Different methods are needed to propagate ignorance and variability. Reliability Engineering and System Safety, 1996 54 : 133 144.
3. Ferson S, Kreinovich V, Ginzburg L, Myers DS, Sentz K. Constructing Probability Boxes and Dempster-Shafer Structures, sand2002-4015. Technical Report, Sandia National Laboratories, Albuquerque, NM, 2002.
4. Dubois D, Prade H. Formal representations of uncertainty. Chapter 3 in Bouyssou D, Dubois D, Pirlot M, Prade H (eds). Decision-Making Process - Concepts and Methods. London : ISTE & Wiley, 2009.
5. Walley P. Statistical Reasoning with Imprecise Probabilities. New York : Chapman and Hall, 1991.
6. Berger J. An overview of robust Bayesian analysis. Test, 1994 3 : 5 124.
7. Dempster A. Upper and lower probabilities induced by a multivalued mapping. Annals of Mathematical Statistics, 1967 38 : 325 339.
8. Shafer G. A Mathematical Theory of Evidence. Princeton, NJ: Princeton University Press, 1976.
9. Dubois D, Prade H. Possibility Theory. New York : Plenum Press, 1988.
10. Dubois D. Possibility theory and statistical reasoning. Computational Statistics & Data Analysis, 2006 51(1) : 47 69.
11. Shafer G, Vovk V. Probability and Finance: It's Only a Game New York : Wiley, 2001.
12. Dubois D, Nguyen HT, Prade H. Possibility theory, probability and fuzzy sets: Misunderstandings, bridges and gaps. Pp. 343-438 in Dubois D, Prade H (eds). Fundamentals of Fuzzy Sets, The Handbooks of Fuzzy Sets Series. Boston, MA : Kluwer, 2000.
13. Dubois D, Prade H. The three semantics of fuzzy sets. Fuzzy Sets and Systems, 1997 90(2) : 141 150.
14. Shackle GLS. Decision, Order and Time in Human Affairs, 2nd ed. Cambridge, UK : Cambridge University Press, 1961.
15. Zadeh LA. Fuzzy sets as a basis for a theory of possibility. Fuzzy Sets and Systems, 1978 1 : 3 28.
16. Hacking I. The Emergence of Probability. Cambridge, UK : Cambridge University Press, 1975.
17. Edwards WF. Likelihood. Cambridge, UK : Cambridge University Press, 1972.
18. Dubois D, Prade H, Smets P. Representing partial ignorance. IEEE Transactions on Systems, Man and Cybernetics, 1996 26(3) : 361 377.
19. Dubois D, Prade H, Smets P. A definition of subjective possibility. International Journal of Approximate Reasoning, 2008 48 : 352 364.
20. Baudrit C, Dubois D. Practical representations of incomplete probabilistic knowledge. Computational Statistics and Data Analysis, 2006 51(1) : 86 108.
21. Baudrit C, Guyonnet D, Dubois D. Joint propagation and exploitation of probabilistic and possibilistic information in risk assessment. IEEE Transactions on Fuzzy Systems, 2006 14 : 593 608.
22. Baudrit C, Guyonnet D, Dubois D. Joint propagation of variability and imprecision in assessing the risk of groundwater contamination. Journal of Contaminant Hydrology, 2007 93 (1-4 72 84.
23. Williamson RC, Downs T. Probabilistic arithmetic I: Numerical methods for calculating convolutions and dependency bounds. International Journal of Approximate Reasoning, 1990 4 : 8 158.
24. Nelsen RB. An introduction to copulas. Vol. 139, Lecture Notes in Statistics. New York : Springer-Verlag, 1999.
25. Dubois D, Kerre E, Mesiar R, Prade H. Fuzzy interval analysis. Pp. 483 581 in Dubois D, Prade H (eds). Fundamentals of Fuzzy Sets. Boston : Kluwer, 2000.
26. Baudrit C, Dubois D. Comparing methods for joint objective and subjective uncertainty propagation with an example in a risk assessment. In Proceedings of Fourth International Symposium on Imprecise Probabilities and Their Application (ISIPTA'05), Pittsburgh, PA, USA, 2005, 31 40.
27. Destercke S, Chojnacki E. Methods for the evaluation and synthesis of multiple sources of information applied to nuclear computer codes. Nuclear Engineering and Design, 2008 238(9) : 2484 2493.
28. 2, Longyearbyen, Svalbard, 2009.
29. Chateauneuf A, Cohen M. Cardinal extensions of the EU model based on Choquet integral. In Chapter 3, Bouyssou D, Dubois D, Pirlot M, Prade H (eds). Decision-Making Process - Concepts and Methods. London : ISTE & Wiley, 2009.
30. Troffaes M. Decision making under uncertainty using imprecise probabilities. International Journal of Approximate Reasoning, 2007 45(1) : 17 29.
31. Gilboa I, Schmeidler D. Maxmin expected utility with a non-unique prior. Journal of Mathematical Economics, 1989 18 : 141 153.
32. Jaffray J-Y. Linear utility theory for belief functions. Operations Research Letters, 1989 8 : 107 112.
33. Guyonnet D, Bellenfant G, Bouc O. Soft methods for treating uncertainties: Applications in the field of environmental risks. Pp. 16 26 in Dubois D, Lubiano MA, Prade H, Gil MA, Grzegorzewski P, Hryniewicz O (eds). SMPS, Vol. 48, Advances in Soft Computing. Berlin : Springer, 2008.