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Space-Fractional Versions of the Negative Binomial and Polya-Type Processes

机译:负二项式和Polya型过程的空间分数型材

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In this paper, we introduce a space fractional negative binomial process (SFNB) by time-changing the space fractional Poisson process by a gamma subordinator. Its one-dimensional distributions are derived in terms of generalized Wright functions and their governing equations are obtained. It is a Levy process and the corresponding Levy measure is given. Extensions to the case of distributed order SFNB, where the fractional index follows a two-point distribution, are investigated in detail. The relationship with space fractional Polya-type processes is also discussed. Moreover, we define and study multivariate versions, which we obtain by time-changing a d-dimensional space-fractional Poisson process by a common independent gamma subordinator. Some applications to population's growth and epidemiology models are explored. Finally, we discuss algorithms for the simulation of the SFNB process.
机译:在本文中,我们通过伽玛下属时间通过时间改变空间分数泊松过程来引入空间分数负二进制过程(SFNB)。 其一维分布是在广义赖特函数方面推导的,并且获得了它们的控制方程。 这是一个征收过程,给出了相应的征收度量。 详细研究了分布式顺序SFNB的延伸,其中分数指数遵循两点分布。 还讨论了与空间分数多地型过程的关系。 此外,我们定义和研究多变量版本,我们通过时间改变一个公共独立的伽马属性的D维空间 - 分数泊松过程获得。 探讨了人口增长和流行病学模型的一些应用。 最后,我们讨论用于模拟SFNB过程的算法。

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