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.
引用
收藏
页数:29
相关论文
共 50 条
  • [31] Functional Limit Theorems for the Fractional Ornstein-Uhlenbeck Process
    Gehringer, Johann
    Li, Xue-Mei
    JOURNAL OF THEORETICAL PROBABILITY, 2022, 35 (01) : 426 - 456
  • [32] Dynamical large deviations of the fractional Ornstein-Uhlenbeck process
    Valov, Alexander
    Meerson, Baruch
    JOURNAL OF PHYSICS A-MATHEMATICAL AND THEORETICAL, 2025, 58 (09)
  • [33] Parameter estimation for the non-stationary Ornstein-Uhlenbeck process with linear drift
    Jiang, Hui
    Dong, Xing
    STATISTICAL PAPERS, 2015, 56 (01) : 257 - 268
  • [34] Least squares estimator for the parameter of the fractional Ornstein-Uhlenbeck sheet
    Clarke De la Cerda, Jorge
    Tudor, Ciprian A.
    JOURNAL OF THE KOREAN STATISTICAL SOCIETY, 2012, 41 (03) : 341 - 350
  • [35] Fractional iterated Ornstein-Uhlenbeck Processes
    Kalemkerian, Juan
    Rafael Leon, Jose
    ALEA-LATIN AMERICAN JOURNAL OF PROBABILITY AND MATHEMATICAL STATISTICS, 2019, 16 (02): : 1105 - 1128
  • [36] Parameter least-squares estimation for time-inhomogeneous Ornstein-Uhlenbeck process
    Pramesti, Getut
    MONTE CARLO METHODS AND APPLICATIONS, 2023, 29 (01): : 1 - 32
  • [37] Fractional Ornstein-Uhlenbeck Process with Stochastic Forcing, and its Applications
    Giacomo Ascione
    Yuliya Mishura
    Enrica Pirozzi
    Methodology and Computing in Applied Probability, 2021, 23 : 53 - 84
  • [38] Fractional Ornstein-Uhlenbeck Process with Stochastic Forcing, and its Applications
    Ascione, Giacomo
    Mishura, Yuliya
    Pirozzi, Enrica
    METHODOLOGY AND COMPUTING IN APPLIED PROBABILITY, 2021, 23 (01) : 53 - 84
  • [39] On integration by parts formula and characterization of fractional Ornstein-Uhlenbeck process
    Sun, Xiaoxia
    Guo, Feng
    STATISTICS & PROBABILITY LETTERS, 2015, 107 : 170 - 177
  • [40] Modeling and forecasting realized volatility with the fractional Ornstein-Uhlenbeck process✩
    Wang, Xiaohu
    Xiao, Weilin
    Yu, Jun
    JOURNAL OF ECONOMETRICS, 2023, 232 (02) : 389 - 415