Fast and asymptotically efficient estimation in the Hawkes processes

被引：0
作者：
Alexandre Brouste
Christian Farinetto
机构：
[1] Le Mans Université,Laboratoire Manceau de Mathématiques
来源：
Japanese Journal of Statistics and Data Science | 2023年 / 6卷
关键词：
Hawkes processes; Le Cam one-step estimation; Maximum-likelihood estimator; Moment estimator;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Fast and asymptotically efficient methods for the estimation of the parameters in self-excited counting Hawkes processes are considered. They are based on the Le Cam one-step estimation procedure. An initial guess estimator is given to estimate both the intensity baseline and the parameters of the kernel of the Hawkes process which characterize the influence of an event on the intensity. Then, the estimation is corrected by a single step of a Newton-type gradient-descent algorithm on the loglikelihood function. Asymptotic properties of the one-step estimators are studied. Monte Carlo simulations show the performance of the procedures for finite size samples in terms of computing time and efficiency. The methodology is finally used to study the claim frequency in building insurance.
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页码：361 / 379
页数：18
相关论文
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