Model and data limitations:The sources and implications of epistemic uncertainty
Model and data limitations:The sources and implications of epistemic uncertainty
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模型和数据的局限性：认知不确定性的来源和影响
DOI：
10.1017/cbo9781139047562.004
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发表时间：
2013
期刊：
影响因子：
--
通讯作者：
K. Beven
中科院分区：
文献类型：
--
作者：
J. Rougier;K. Beven
第 2 章完全关注偶然的不确定性。这是由于危险本身的随机性而产生的不确定性，也可能是由于对危险结果的反应而产生的。该章通过足迹函数和损失算子追踪了这种不确定性，得出了超出概率 (EP) 曲线。这种结构化方法（例如，与纯粹的统计方法相反）的动机是需要评估不同的干预措施以在不同的行动之间进行选择；以及以数十年为单位衡量的政策相关时间尺度上边界条件非平稳的可能性。不同的风险管理者会有不同的损失算子，因此也会有不同的 EP 曲线。同样，同一风险经理针对不同的行动也会有不同的 EP 曲线。 EP 曲线的一个非常简单的汇总统计量是其下方的面积，它对应于预期损失（数学意义上的“预期”），其定义为风险。
Chapter 2 focused entirely on aleatory uncertainty. This is the uncertainty that arises out of the randomness of the hazard itself, and also, possibly, out of the responses to the hazard outcome. That chapter chased this uncertainty through the footprint function and a loss operator to arrive at an exceedance probability (EP) curve. Such a structured approach (e.g. as opposed to a purely statistical approach) was motivated by the need to evaluate different interventions for choosing between different actions; and by the possibility of non-stationarity in the boundary conditions on policy-relevant timescales measured in decades. Different risk managers will have different loss operators, and hence different EP curves. Likewise, the same risk manager will have different EP curves for different actions. A very simple summary statistic of an EP curve is the area underneath it, which corresponds to the expected loss (‘expectation’ taken in the mathematical sense), which is defined to be the risk.
影响因子：
0.9
作者：
Goldstein, Michael;Rougier, Jonathan
通讯作者：
Rougier, Jonathan