The Scenario Weights for Importance Measurement (SWIM) package implements a flexible sensitivity analysis framework, based primarily on results and tools developed by Pesenti et al. (2019). SWIM provides a stressed version of a stochastic model, subject to model components (random variables) fulfilling given probabilistic constraints (stresses). Possible stresses can be applied on moments, probabilities of given events, and risk measures such as Value-At-Risk and Expected Shortfall. SWIM operates upon a single set of simulated scenarios from a stochastic model, returning scenario weights, which encode the required stress and allow monitoring the impact of the stress on all model components. The scenario weights are calculated to minimise the relative entropy with respect to the baseline model, subject to the stress applied. As well as calculating scenario weights, the package provides tools for the analysis of stressed models, including plotting facilities and evaluation of sensitivity measures. SWIM does not require additional evaluations of the simulation model or explicit knowledge of its underlying statistical and functional relations; hence, it is suitable for the analysis of black box models. The capabilities of SWIM are demonstrated through a case study of a credit portfolio model.

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重要性测量的情景权重 (SWIM) – 用于敏感性分析的 R 包

重要性测量的情景权重 (游泳) 包实现了一个灵活的敏感性分析框架，主要基于 Pesenti 开发的结果和工具等人. （2019）。游泳提供随机模型的受压版本，受模型组件（随机变量）的约束，满足给定的概率约束（应力）。可能的压力可以应用于给定事件的时刻、概率和风险度量，例如风险价值和预期短缺。游泳对来自随机模型的一组模拟场景进行操作，返回场景权重，这些权重对所需的压力进行编码并允许监控压力对所有模型组件的影响。计算情景权重以最小化相对于基线模型的相对熵，受施加的压力影响。除了计算情景权重外，该软件包还提供用于分析压力模型的工具，包括绘图设施和敏感性测量评估。游泳不需要对仿真模型进行额外评估或明确了解其基础统计和函数关系；因此，它适用于黑盒模型的分析。的能力游泳通过一个信贷组合模型的案例研究来证明。