Practical representations of incomplete probabilistic knowledge
Practical representations of incomplete probabilistic knowledge
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DOI：
10.1016/j.csda.2006.02.009
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发表时间：
2006-11-01
影响因子：
1.8
通讯作者：
Dubois, D.
中科院分区：
文献类型：
--
作者：
Baudrit, C.;Dubois, D.
不完整的概率知识，可以遇到风险评估问题，例如在环境研究的紧凑表示。各种知识被认为是如专家意见的分布特性或统计信息差。该方法是基于概率家族编码的可能性分布和信念功能。在每种情况下，提出了一种技术，用于忠实地表示可用的不精确的概率信息，使用不同的不确定性框架，如可能性理论，概率论，和信念函数等。此外，使用概率-可能性变换，使置信区间所包含的可能性分布的削减，从而使表示更强。分别适当的对累积分布，连续的可能性分布或离散的随机集表示的平均值，模式，中位数和其他分位数的不知名的概率分布的信息进行了详细讨论。(C)2006 Elsevier B. V.保留所有权利。
The compact representation of incomplete probabilistic knowledge which can be encountered in risk evaluation problems, for instance in environmental studies is considered. Various kinds of knowledge are considered such as expert opinions about characteristics of distributions or poor statistical information. The approach is based on probability families encoded by possibility distributions and belief functions. In each case, a technique for representing the available imprecise probabilistic information faithfully is proposed, using different uncertainty frameworks, such as possibility theory, probability theory, and belief functions, etc. Moreover the use of probability-possibility transformations enables confidence intervals to be encompassed by cuts of possibility distributions, thus making the representation stronger. The respective appropriateness of pairs of cumulative distributions, continuous possibility distributions or discrete random sets for representing information about the mean value, the mode, the median and other fractiles of ill-known probability distributions is discussed in detail. (C) 2006 Elsevier B.V. All rights reserved.