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arXiv 1610.03300math.PR
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记忆核为Erlang核之和的非线性Hawkes过程的稳定性、收敛性及模拟

Stability, convergence to equilibrium and simulation of non-linear Hawkes Processes with memory kernels given by the sum of Erlang kernels

Aline Duarte, Eva Löcherbach, Guilherme Ost

摘要:

考虑记忆核由Erlang核之和给出的非线性Hawkes过程。它表明,它们的稳定性可以研究在相关的一类分段确定性马尔可夫过程,称为马尔可夫级联的连续记忆条款。明确的条件暗示这些过程的积极哈里斯复发。证明是基于关于跳跃时间的部分分部积分法。一个重要的性质是过渡半群的非退化性,这是由于相关的Vandermonde矩阵的可逆性而获得的。对于Lipschitz连续率函数,我们还表明,这些马尔可夫级联收敛到平衡指数快速相对于Wasserstein距离。最后,经典细化算法的扩展,提出了模拟这样的马尔可夫级联。

英文摘要:

Non-linear Hawkes processes with memory kernels given by the sum of Erlang kernels are considered. It is shown that their stability properties can be studied in terms of an associated class of piecewise deterministic Markov processes, called Markovian cascades of successive memory terms. Explicit conditions implying the positive Harris recurrence of these processes are presented. The proof is based on integration by parts with respect to the jump times. A crucial property is the non-degeneracy of the transition semigroup which is obtained thanks to the invertibility of an associated Vandermonde matrix. For Lipschitz continuous rate functions we also show that these Markovian cascades converge to equilibrium exponentially fast with respect to the Wasserstein distance. Finally, an extension of the classical thinning algorithm is proposed to simulate such Markovian cascades.

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