期刊
RELIABILITY ENGINEERING & SYSTEM SAFETY
卷 85, 期 1-3, 页码 239-248出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.ress.2004.03.014
关键词
aleatory probability; Bayesian inference; computer codes; elicitaton; epistemic probability; sensitivity analysis; sources of uncertainty; uncertainty analysis
There are difficulties with probability as a representation of uncertainty. However, we argue that there is an important distinction between principle and practice. In principle, probability is uniquely appropriate for the representation and quantification of all forms of uncertainty; it is in this sense that we claim that 'probability is perfect'. In practice, people find it difficult to express their knowledge and beliefs in probabilistic form, so that elicitation of probability distributions is a far from perfect process. We therefore argue that there is no need for alternative theories, but that any practical elicitation of expert knowledge must fully acknowledge imprecision in the resulting distribution. We outline a recently developed Bayesian technique that allows the imprecision in elicitation to be formulated explicitly, and apply it to some of the challenge problems. (C) 2004 Elsevier Ltd. All rights reserved.
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