卷积分数泊松过程

K. K. Kataria, M. Khandakar
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引用次数: 7

摘要

本文通过对控制其状态概率的分数阶微分方程系统中空间变量的离散卷积,引入并研究了时间分数阶泊松过程的一个卷积版本。我们把引入的过程称为卷积分数泊松过程(CFPP)。得到其状态概率的拉普拉斯变换的显式表达式,其反演得到其一维分布。得到了它的一些统计性质,如概率生成函数、矩生成函数、矩等。本文研究了绕泊松过程的一个特例,即绕泊松过程,并讨论了它与绕泊松过程随时间变化的隶属关系。证明了CPP是一个Levy过程,利用它建立了CFPP的长程相关性质。此外,我们还证明了CFPP的增量具有短期依赖性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Convoluted Fractional Poisson Process
In this paper, we introduce and study a convoluted version of the time fractional Poisson process by taking the discrete convolution with respect to space variable in the system of fractional differential equations that governs its state probabilities. We call the introduced process as the convoluted fractional Poisson process (CFPP). The explicit expression for the Laplace transform of its state probabilities are obtained whose inversion yields its one-dimensional distribution. Some of its statistical properties such as probability generating function, moment generating function, moments etc. are obtained. A special case of CFPP, namely, the convoluted Poisson process (CPP) is studied and its time-changed subordination relationships with CFPP are discussed. It is shown that the CPP is a Levy process using which the long-range dependence property of CFPP is established. Moreover, we show that the increments of CFPP exhibits short-range dependence property.
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