Parameter estimation for the Rosenblatt Ornstein–Uhlenbeck process with periodic mean

被引：0
|
作者：
Radomyra Shevchenko
Ciprian A. Tudor
机构：
[1] TU Dortmund,Fakultät für Mathematik, LSIV
[2] CNRS,Laboratoire Paul Painlevé UMR 8524
[3] Université de Lille,ISMMA
[4] Romanian Academy,undefined
来源：
Statistical Inference for Stochastic Processes | 2020年 / 23卷
关键词：
Rosenblatt process; Parameter estimation; Malliavin calculus; Multiple Wiener–Itô integrals; Strong consistency; Asymptotic normality; Ornstein–Uhlenbeck process; Periodic mean function; Least squares estimator; 60H15; 60H07; 60G35;
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学科分类号：
摘要：
We study the least squares estimator for the drift parameter of the Langevin stochastic equation driven by the Rosenblatt process. Using the techniques of the Malliavin calculus and the stochastic integration with respect to the Rosenblatt process, we analyze the consistency and the asymptotic distribution of this estimator. We also introduce alternative estimators, which can be simulated, and we study their asymptotic properties.
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页码：227 / 247
页数：20
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