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Poisson Process Driven Stochastic Differential Equations for bivariate heavy tailed distributions

机译:二元重尾分布的Poisson过程驱动随机微分方程

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Stochastic differential equations have been used intensively in stochastic control. In this paper, we present 2-dimensional Poisson Counter Driven Stochastic Differential Equation (PCSDE) models that lead to correlated bivariated power law behaviors. We propose two types of 2D PCSDE models and study their tail dependence behavior. The first model generates tail dependence coefficient with values either 0 or 1; while the second model could have the values between 0 and 1. We discuss plausible application of our models in complex network generative models.
机译:随机微分方程已广泛用于随机控制中。在本文中,我们提出了二维Poisson计数器驱动的随机微分方程(PCSDE)模型,该模型导致了相关的双变量幂律行为。我们提出了两种类型的2D PCSDE模型,并研究了它们的尾部依赖行为。第一个模型生成尾部相关系数,其值为0或1。而第二个模型的值可以在0到1之间。我们讨论了我们的模型在复杂网络生成模型中的合理应用。

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