Quantification of margins and uncertainties: Alternative representations of epistemic uncertainty
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[1] G. Klir. Measure of Uncertainty and Information , 2006 .
[2] George J. Klir,et al. Uncertainty-Based Information , 1999 .
[3] Jon C. Helton,et al. Quantification of margins and uncertainties: Conceptual and computational basis , 2011, Reliab. Eng. Syst. Saf..
[4] Philippe Smets,et al. Probability, Possibility, Belief: Which and Where? , 1998 .
[5] O. Kallenberg. Foundations of Modern Probability , 2021, Probability Theory and Stochastic Modelling.
[6] S. Kaplan,et al. On The Quantitative Definition of Risk , 1981 .
[7] G. Apostolakis. The concept of probability in safety assessments of technological systems. , 1990, Science.
[8] J. Fodor,et al. Evaluation of Uncertainties and Risks in Geology , 2004 .
[9] Nic Wilson,et al. Markov Chain Monte-Carlo Algorithms for the Calculation of Dempster-Shafer Belief , 1994, AAAI.
[10] Scott Ferson,et al. Constructing Probability Boxes and Dempster-Shafer Structures , 2003 .
[11] J. Kacprzyk,et al. Advances in the Dempster-Shafer theory of evidence , 1994 .
[12] Didier Dubois,et al. Possibility Theory - An Approach to Computerized Processing of Uncertainty , 1988 .
[13] Didier Dubois,et al. Practical representations of incomplete probabilistic knowledge , 2006, Comput. Stat. Data Anal..
[14] Jon C. Helton,et al. Sensitivity analysis in conjunction with evidence theory representations of epistemic uncertainty , 2006, Reliab. Eng. Syst. Saf..
[15] F. O. Hoffman,et al. Propagation of uncertainty in risk assessments: the need to distinguish between uncertainty due to lack of knowledge and uncertainty due to variability. , 1994, Risk analysis : an official publication of the Society for Risk Analysis.
[16] Jon C. Helton,et al. Treatment of Uncertainty in Performance Assessments for Complex Systems , 1994 .
[17] W. Woodall,et al. A probabilistic and statistical view of fuzzy methods , 1995 .
[18] Da Ruan,et al. Foundations and Applications of Possibility Theory , 1995 .
[19] I. Hacking. An Introduction to Probability and Inductive Logic , 2001 .
[20] Lotfi A. Zadeh,et al. Fuzzy Sets , 1996, Inf. Control..
[21] Vladik Kreinovich,et al. Convergence properties of an interval probabilistic approach to system reliability estimation , 2005, Int. J. Gen. Syst..
[22] D. Bell,et al. Evidence Theory and Its Applications , 1991 .
[23] Peter Urbach,et al. Scientific Reasoning: The Bayesian Approach , 1989 .
[24] L. Zadeh. Fuzzy sets as a basis for a theory of possibility , 1999 .
[25] Luc Jaulin,et al. Applied Interval Analysis , 2001, Springer London.
[26] R. B. Kearfott,et al. Applications of interval computations , 1996 .
[27] Ramon E. Moore. Methods and applications of interval analysis , 1979, SIAM studies in applied mathematics.
[28] J. Kohlas. Modeling uncertainty with belief functions in numerical models , 1989 .
[29] C. T. Haan. Parametric Uncertainty in Hydrologic Modeling , 1989 .
[30] J. C. Helton,et al. Uncertainty and sensitivity analysis in the presence of stochastic and subjective uncertainty , 1997 .
[31] William Feller,et al. An Introduction to Probability Theory and Its Applications , 1951 .
[32] Jon C. Helton,et al. Representation of analysis results involving aleatory and epistemic uncertainty , 2010, Int. J. Gen. Syst..
[33] A. Neumaier. Interval methods for systems of equations , 1990 .
[34] Jay D. Johnson,et al. Competing Failure Risk Analysis Using Evidence Theory , 2005, Risk analysis : an official publication of the Society for Risk Analysis.
[35] V. Kreinovich,et al. Monte-Carlo methods make Dempster-Shafer formalism feasible , 1994 .
[36] George J. Klir,et al. On the alleged superiority of probabilistic representation of uncertainty , 1994, IEEE Trans. Fuzzy Syst..
[37] T. Fine. Theories of Probability: An Examination of Foundations , 1973 .
[38] Jon Craig Helton,et al. Conceptual and computational basis for the quantification of margins and uncertainty. , 2009 .
[39] L. Wasserman. Belief functions and statistical inference , 1990 .
[40] G. Apostolakis,et al. Uncertainties in system analysis: Probabilistic versus nonprobabilistic theories , 1990 .
[41] Ronald Fagin,et al. Two Views of Belief: Belief as Generalized Probability and Belief as Evidence , 1992, Artif. Intell..
[42] B. Kosko. Fuzziness vs. probability , 1990 .
[43] David Lindley. Scoring rules and the inevitability of probability , 1982 .
[44] H. Fineberg,et al. Understanding Risk: Informing Decisions in a Democratic Society , 1996 .
[45] G. Klir. IS THERE MORE TO UNCERTAINTY THAN SOME PROBABILITY THEORISTS MIGHT HAVE US BELIEVE , 1989 .
[46] Robert L. Winkler,et al. Uncertainty in probabilistic risk assessment , 1996 .
[47] Roy Weatherford,et al. Philosophical Foundations of Probability Theory , 2022 .
[48] D. Dubois,et al. Fuzzy sets, probability and measurement , 1989 .
[49] Glenn Shafer,et al. A Mathematical Theory of Evidence , 2020, A Mathematical Theory of Evidence.
[50] Eduard Hofer,et al. When to separate uncertainties and when not to separate , 1996 .
[51] Didier Dubois,et al. Possibility Theory: Qualitative and Quantitative Aspects , 1998 .
[52] Peter C. Cheeseman,et al. An inquiry into computer understanding , 1988, Comput. Intell..
[53] Da Ruan,et al. Foundations and applications of possibility theory : proceedings of FAPT '95 : Ghent, Belgium, 13-15 December 1995 , 1995 .
[54] S. Ferson,et al. Different methods are needed to propagate ignorance and variability , 1996 .
[55] G. Cooman. POSSIBILITY THEORY I: THE MEASURE- AND INTEGRAL-THEORETIC GROUNDWORK , 1997 .
[56] G. W. Parry,et al. Characterization and evaluation of uncertainty in probabilistic risk analysis , 1981 .
[57] Ian Hacking,et al. The Emergence of Probability. A Philosophical Study of Early Ideas about Probability, Induction and Statistical Inference , 1979 .
[58] Jon C. Helton,et al. Quantification of margins and uncertainties: Example analyses from reactor safety and radioactive waste disposal involving the separation of aleatory and epistemic uncertainty , 2011, Reliab. Eng. Syst. Saf..
[59] M. Elisabeth Paté-Cornell,et al. Uncertainties in risk analysis: Six levels of treatment , 1996 .
[60] D. Dubois,et al. Fundamentals of fuzzy sets , 2000 .
[61] A. Dempster. Upper and lower probability inferences based on a sample from a finite univariate population. , 1967, Biometrika.
[62] J. C. Helton,et al. Bounds on belief and plausibility of functionally propagated random sets , 2002, 2002 Annual Meeting of the North American Fuzzy Information Processing Society Proceedings. NAFIPS-FLINT 2002 (Cat. No. 02TH8622).
[63] P. Billingsley,et al. Probability and Measure , 1980 .
[64] Jon C. Helton,et al. Guest editorial: treatment of aleatory and epistemic uncertainty in performance assessments for complex systems , 1996 .
[65] C. Howson,et al. Scientific Reasoning: The Bayesian Approach , 1989 .
[66] Arthur P. Dempster,et al. Upper and Lower Probabilities Induced by a Multivalued Mapping , 1967, Classic Works of the Dempster-Shafer Theory of Belief Functions.
[67] Thomas Kämpke. About assessing and evaluating uncertain inferences within the theory of evidence , 1988, Decis. Support Syst..
[68] Jon C. Helton,et al. An exploration of alternative approaches to the representation of uncertainty in model predictions , 2003, Reliab. Eng. Syst. Saf..
[69] Arthur P. Dempster,et al. A Generalization of Bayesian Inference , 1968, Classic Works of the Dempster-Shafer Theory of Belief Functions.
[70] A. Kiureghian,et al. Aleatory or epistemic? Does it matter? , 2009 .
[71] David Lindley,et al. The Probability Approach to the Treatment of Uncertainty in Artificial Intelligence and Expert Systems , 1987 .
[72] R. Ash,et al. Probability and measure theory , 1999 .
[73] Hung T. Nguyen,et al. Possibility Theory, Probability and Fuzzy Sets Misunderstandings, Bridges and Gaps , 2000 .
[74] William Feller,et al. An Introduction to Probability Theory and Its Applications , 1967 .
[75] Dov M. Gabbay,et al. Handbook of defeasible reasoning and uncertainty management systems: volume 2: reasoning with actual and potential contradictions , 1998 .
[76] Jay D. Johnson,et al. A sampling-based computational strategy for the representation of epistemic uncertainty in model predictions with evidence theory , 2007 .
[77] Jon C. Helton,et al. Probability, conditional probability and complementary cumulative distribution functions in performance assessment for radioactive waste disposal , 1996 .
[78] R. Keeney,et al. Improving risk communication. , 1986, Risk analysis : an official publication of the Society for Risk Analysis.
[79] Stephen M. Stigler. The History of Statistics: The Measurement of Uncertainty before 1900 , 1986 .
[80] Kari Sentz,et al. Combination of Evidence in Dempster-Shafer Theory , 2002 .