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Optimal Threshold Determination for the Maximum Product of Spacing Methodology with Ties for Extreme Events

机译:具有极端事件联系的间隔方法的最大乘积的最佳阈值确定

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Extreme events are defined as values of the event below or above a certain value called threshold. A well chosen threshold helps to identify the extreme levels. Several methods have been used to determine threshold so as to analyze and model extreme events. One of the most successful methods is the maximum product of spacing (MPS). However, there is a problem encountered while modeling data through this method in that the method breaks down when there is a tie in the exceedances. This study offers a solution to model data even if it contains ties. To do so, an optimal threshold that gives more optimal parameters for extreme events, was determined. The study achieved its main objective by deriving a method that improved MPS method for determining an optimal threshold for extreme values in a data set containing ties, estimated the Generalized Pareto Distribution (GPD) parameters for the optimal threshold derived and compared these GPD parameters with GPD parameters determined through the standard MPS model. The study improved maximum product of spacing method and used Generalized Pareto Distribution (GPD) and Peak over threshold (POT) methods as the basis of identifying extreme values. This study will help the statisticians in different sectors of our economy to model extreme events involving ties. To statisticians, the structure of the extreme levels which exist in the tails of the ordinary distributions is very important in analyzing, predicting and forecasting the likelihood of an occurrence of the extreme event.
机译:极端事件定义为事件值低于或高于某个值(称为阈值)。正确选择的阈值有助于确定极端水平。已经使用了几种方法来确定阈值,以便对极端事件进行分析和建模。最成功的方法之一是最大间距产品(MPS)。但是,通过这种方法对数据进行建模时会遇到一个问题,即当超出范围时,该方法就会失效。这项研究提供了一种对数据建模的解决方案,即使该数据包含联系也是如此。为此,确定了为极端事件提供更多最佳参数的最佳阈值。通过达到以下目的,本研究实现了其主要目标:改进的MPS方法,用于确定包含联系的数据集中的极值的最佳阈值,估计导出的最佳阈值的广义帕累托分布(GPD)参数,并将这些GPD参数与GPD进行比较通过标准MPS模型确定的参数。该研究提高了间距法的最大乘积,并使用广义帕累托分布(GPD)和峰值超过阈值(POT)方法作为识别极值的基础。这项研究将帮助我们经济各部门的统计学家对涉及联系的极端事件进行建模。对于统计学家来说,存在于常态分布尾部的极端水平结构对于分析,预测和预测极端事件发生的可能性非常重要。

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