We characterize a Hawkes point process with kernel proportional to the probability density function of Mittag-Leffler random variables. This kernel decays as a power law with exponent β + 1 ∈ (1, 2]. Several analytical results can be proved, in particular for the expected intensity of the point process and for the expected number of events of the counting process. These analytical results are used to validate algorithms that numerically invert the Laplace transform of the expected intensity as well as Monte Carlo simulations of the process. Finally, Monte Carlo simulations are used to derive the full distribution of the number of events. The algorithms used for this paper are available at https://github.com/habyarimanacassien/Fractional-Hawkes.
A fractional Hawkes process II: Further characterization of the process / Habyarimana, Cassien; Aduda, Jane A.; Scalas, Enrico; Chen, Jing; Hawkes, Alan G.; Polito, Federico. - In: PHYSICA. A. - ISSN 0378-4371. - 615:(2023), pp. 1-11. [10.1016/j.physa.2023.128596]
A fractional Hawkes process II: Further characterization of the process
Enrico Scalas
;Federico Polito
2023
Abstract
We characterize a Hawkes point process with kernel proportional to the probability density function of Mittag-Leffler random variables. This kernel decays as a power law with exponent β + 1 ∈ (1, 2]. Several analytical results can be proved, in particular for the expected intensity of the point process and for the expected number of events of the counting process. These analytical results are used to validate algorithms that numerically invert the Laplace transform of the expected intensity as well as Monte Carlo simulations of the process. Finally, Monte Carlo simulations are used to derive the full distribution of the number of events. The algorithms used for this paper are available at https://github.com/habyarimanacassien/Fractional-Hawkes.File | Dimensione | Formato | |
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