Asymptotic properties for the parameter estimation in Ornstein-Uhlenbeck process with discrete observations

被引:11
|
作者
Jiang, Hui [1 ]
Liu, Hui [1 ]
Zhou, Youzhou [2 ]
机构
[1] Nanjing Univ Aeronaut & Astronaut, Dept Math, Nanjing 211106, Peoples R China
[2] Xian Jiaotong Liverpool Univ, Dept Pure Math, Suzhou 215123, Peoples R China
来源
ELECTRONIC JOURNAL OF STATISTICS | 2020年 / 14卷 / 02期
基金
中国国家自然科学基金;
关键词
Ornstein-Uhlenbeck process; discrete observations; moderate deviation principle; multiple Wiener-Ito integrals; BERRY-ESSEEN BOUNDS; LEAST-SQUARES ESTIMATOR; MODERATE DEVIATIONS; LONG-MEMORY; DIFFUSION; INFERENCE; INEQUALITIES; CONSISTENCY; INTEGRALS; BEHAVIOR;
D O I
10.1214/20-EJS1738
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
In this paper, under discrete observations, we study Cramer-type moderate deviations (extended central limit theorem) for parameter estimation in Ornstein-Uhlenbeck process. Our results contain both stationary and explosive cases. For applications, we propose test statistics which can be used to construct rejection regions in the hypothesis testing for the drift coefficient, and the corresponding probability of type II error tends to zero exponentially. Simulation study shows that our test statistics have good finite-sample performances both in size and power. The main methods include the deviation inequalities for multiple Wiener-Ito integrals, as well as the asymptotic analysis techniques.
引用
收藏
页码:3192 / 3229
页数:38
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