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arXiv 2005.11167math.PR
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卷积分式泊松过程

Convoluted Fractional Poisson Process

K. K. Kataria, M. Khandakar

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的空间变量进行离散卷积,引入并研究了时间分数阶泊松过程的卷积形式.我们称引入的过程为卷积分数泊松过程(CFPP)。得到了其状态概率的拉普拉斯变换的显式表达式,其逆变换得到其一维分布。得到了它的一些统计性质,如概率母函数、矩母函数、矩等。研究了CFPP的一种特殊情况,即卷积泊松过程(CPP),讨论了CPP与CFPP的时变隶属关系。证明了CPP是一个Lévy过程,并由此建立了CFPP的长程相关性。此外,我们还证明了CFPP的增量具有短程依赖性。

英文摘要:

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 Lévy 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.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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