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Statistical detection and classification of background risks affecting inputs and outputs

机译:统计检测和分类影响输入和输出的背景风险

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摘要

Systems are exposed to a variety of risks, including those known as background or systematic risks. Therefore, advanced economic, financial, and engineering models incorporate such risks, thus inevitably making the models more challenging to explore. A number of natural questions arise. First and foremost, is the given system affected by any of such risks? If so, then is the system affected by the risks at the input or output stage, or at both stages? In the present paper we construct an algorithm that answers such questions. Even though the algorithm is based on intricate probabilistic considerations, its practical implementation is easy.
机译:系统面临各种风险,包括称为背景风险或系统风险。因此,先进的经济,金融和工程模型包含了此类风险,因此不可避免地使模型的探索更具挑战性。出现了许多自然问题。首先,给定系统是否受到任何此类风险的影响?如果是这样,那么系统会受到输入或输出阶段或两个阶段的风险的影响吗?在本文中,我们构造了一种可以回答此类问题的算法。即使该算法基于复杂的概率考虑因素,其实际实现也很容易。

著录项

  • 来源
    《Metron》 |2019年第1期|1-18|共18页
  • 作者单位

    Faculty of Mathematics and Mechanics, Saint Petersburg State University, Saint Petersburg 199034, Russia;

    School of Mathematical and Statistical Sciences, Western University, London, ON N6A 5B7, Canada;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Input; Output; Background risk; Gini index; Statistical model;

    机译:输入;输出;背景风险;基尼系数统计模型;

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