Self-normalized asymptotic properties for the parameter estimation in fractional Ornstein-Uhlenbeck process

被引:13
|
作者
Jiang, Hui [1 ]
Liu, Junfeng [2 ]
Wang, Shaochen [3 ]
机构
[1] Nanjing Univ Aeronaut & Astronaut, Dept Math, Nanjing 211106, Jiangsu, Peoples R China
[2] Nanjing Audit Univ, Dept Stat, Nanjing 211815, Jiangsu, Peoples R China
[3] South China Univ Technol, Sch Math, Guangzhou 510640, Guangdong, Peoples R China
基金
美国国家科学基金会; 中国国家自然科学基金;
关键词
Deviation inequalities; fractional Ornstein-Uhlenbeck process; hypothesis testing; least squares estimator; moderate deviation principle; multiple Wiener-Ito integrals; CENTRAL LIMIT-THEOREMS; SHARP LARGE DEVIATIONS; MODERATE DEVIATIONS; INEQUALITIES; FUNCTIONALS; INTEGRALS; MAXIMUM;
D O I
10.1142/S0219493719500187
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, we consider the self-normalized asymptotic properties of the parameter estimators in the fractional Ornstein-Uhlenbeck process. The deviation inequalities, Cramer-type moderate deviations and Berry-Esseen bounds are obtained. The main methods include the deviation inequalities and moderate deviations for multiple Wiener-Ito integrals [P. Major, Tail behavior of multiple integrals and U-statistics, Probab. Surv. 2 (2005) 448-505; On a multivariate version of Bernsteins inequality, Electron. J. Probab. 12 (2007) 966-988; M. Schulte and C. Thale, Cumulants on Wiener chaos: Moderate deviations and the fourth moment theorem, J. Funct. Anal. 270(2016) 2223-2248], as well as the Delta methods in large deviations [F. Q. Gao and X. Q. Zhao, Delta method in large deviations and moderate deviations for estimators, Ann. Statist. 39 (2011) 1211-1240]. For applications, we propose two test statistics which can be used to construct confidence intervals and rejection regions in the hypothesis testing for the drift coefficient. It is shown that the Type II errors tend to be zero exponential when using the proposed test statistics.
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页数:29
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