Abstract
Continuous time Markov Chains, Hawkes processes and many other interesting processes can be described as a solution of stochastic differential equations driven by Poisson measures. Previous works, using the Stein’s method, give the convergence rate of a sequence of renormalized Poisson measures toward the Brownian motion in several distances, constructed on the model of the Kantorovitch–Rubinstein (or Wasserstein-1) distance. We show that many operations (like time change, convolution) on continuous functions are Lipschitz continuous to extend these quantified convergences to diffusive limits of Markov processes and long-time behavior of Hawkes processes.
Citation
Eustache Besançon. Laure Coutin. Laurent Decreusefond. Pascal Moyal. "Diffusive limits of Lipschitz functionals of Poisson measures." Ann. Appl. Probab. 34 (1A) 555 - 584, February 2024. https://doi.org/10.1214/23-AAP1972
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