Moment estimators for the parameters of Ornstein-Uhlenbeck processes driven by compound Poisson processes

被引：6

作者：

Wu, Yanfeng ^{[1
]}

Hu, Jianqiang ^{[2
]}

Zhang, Xinsheng ^{[3
]}

机构：

[1] Fudan Univ, Dept Management Sci, 670 Guoshun Rd,Lidasan Bldg, Shanghai 200433, Peoples R China

[2] Fudan Univ, Dept Management Sci, 670 Guoshun Rd,Siyuan Bldg,Room 508, Shanghai 200433, Peoples R China

[3] Fudan Univ, Dept Stat, 670 Guoshun Rd,Siyuan Bldg,Room 719, Shanghai 200433, Peoples R China

来源：

DISCRETE EVENT DYNAMIC SYSTEMS-THEORY AND APPLICATIONS | 2019年 / 29卷 / 01期

基金：

中国国家自然科学基金;

关键词：

Ornstein-Uhlenbeck process; Stochastic hybrid system; Parameter estimation; Method of moments; MAXIMUM-LIKELIHOOD-ESTIMATION; GENERALIZED-METHOD; INFERENCE; MODELS;

D O I：

10.1007/s10626-019-00276-y

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

We develop new estimators for the parameters of Ornstein-Uhlenbeck processes driven by compound Poisson processes, which can be considered as a class of stochastic hybrid systems. Our estimators are derived based on the method of moments. We also establish the central limit theorem for the proposed estimators. Numerical experiments are provided to show that our method performs better when compared with the existing methods, especially in cases when the jumps of the compound Poisson process are relatively rare.

引用

页码：57 / 77

页数：21

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