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Poisson approximation of point processes with stochastic intensity, and application to nonlinear Hawkes processes. (English. French summary) Zbl 1367.60020

Summary: We give a general inequality for the total variation distance between a Poisson distributed random variable and a first order stochastic integral with respect to a point process with stochastic intensity, constructed by embedding in a bivariate Poisson process. We apply this general inequality to first order stochastic integrals with respect to a class of nonlinear Hawkes processes, which is of interest in queueing theory, providing explicit bounds for the Poisson approximation, a quantitative Poisson limit theorem, confidence intervals and asymptotic estimates of the moments.

MSC:

60F05 Central limit and other weak theorems
60G55 Point processes (e.g., Poisson, Cox, Hawkes processes)
60H05 Stochastic integrals
60H07 Stochastic calculus of variations and the Malliavin calculus
60K25 Queueing theory (aspects of probability theory)