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A fractional generalization of the Poisson processes

TLDR
In this article, a non-Markovian renewal process with a waiting time distribution described by the Mittag-Leffler function is analyzed, and it is shown that this distribution plays a fundamental role in the infinite thinning procedure of a generic renewal process governed by a power asymptotic waiting time.
Abstract
It is our intention to provide via fractional calculus a generalization of the pure and compound Poisson processes, which are known to play a fundamental role in renewal theory, without and with reward, respectively. We first recall the basic renewal theory including its fundamental concepts like waiting time between events, the survival probability, the counting function. If the waiting time is exponentially distributed we have a Poisson process, which is Markovian. However, other waiting time distributions are also relevant in applications, in particular such ones with a fat tail caused by a power law decay of its density. In this context we analyze a non-Markovian renewal process with a waiting time distribution described by the Mittag-Leffler function. This distribution, containing the exponential as particular case, is shown to play a fundamental role in the infinite thinning procedure of a generic renewal process governed by a power asymptotic waiting time. We then consider the renewal theory with reward that implies a random walk subordinated to a renewal process.

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The Fractional Poisson Process and the Inverse Stable Subordinator

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Hilfer–Prabhakar derivatives and some applications

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