Asymptotically efficient estimation of Ergodic rough fractional Ornstein-Uhlenbeck process under continuous observations

被引：0

作者：

Chiba, Kohei ^{[1
]}

Takabatake, Tetsuya ^{[2
]}

机构：

[1] Osaka Univ, Grad Sch Engn Sci, 3 Machikaneyama Cho 1 Chome, Toyonaka, Osaka, Japan

[2] Hiroshima Univ, Sch Econ, 2-1 Kagamiyama 1 Chome, Higashihiroshima, Hiroshima, Japan

来源：

STATISTICAL INFERENCE FOR STOCHASTIC PROCESSES | 2024年 / 27卷 / 01期

基金：

日本学术振兴会;

关键词：

Fractional Ornstein-Uhlenbeck process; Estimation of drift parameters; Continuous observations; Local asymptotic normality property;

D O I：

10.1007/s11203-023-09300-3

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：

We consider the problem of asymptotically efficient estimation of drift parameters of the ergodic fractional Ornstein-Uhlenbeck process under continuous observations when the Hurst parameter H < 1/2 and the mean of its stationary distribution is not equal to zero. In this paper, we derive asymptotically efficient rates and variances of estimators of drift parameters and prove an asymptotic efficiency of a maximum likelihood estimator of drift parameters.

引用

页码：103 / 122

页数：20

共 38 条

[1] Asymptotically efficient estimation of Ergodic rough fractional Ornstein-Uhlenbeck process under continuous observations
Kohei Chiba
Tetsuya Takabatake
Statistical Inference for Stochastic Processes, 2024, 27 : 103 - 122
[2] On parameter estimation of fractional Ornstein-Uhlenbeck process
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[9] Self-normalized asymptotic properties for the parameter estimation in fractional Ornstein-Uhlenbeck process
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