罗森布拉特过程驱动的 SDE 的参数估计和路径空间上的奇异规律

IF 1.1 2区 数学 Q3 STATISTICS & PROBABILITY Stochastic Processes and their Applications Pub Date : 2024-10-05 DOI:10.1016/j.spa.2024.104499
Petr Čoupek, Pavel Kříž, Bohdan Maslowski
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引用次数: 0

摘要

在本文中,我们研究了由加性罗森布拉特过程和路径空间上诱导规律的奇异性驱动的(可能是非线性)SDEs 解的参数识别。我们提出了一种漂移参数、扩散强度和赫斯特指数的联合估计器,该估计器可从有界时间跨度的离散时间观测结果中计算得出。由于这种强一致性,不同漂移的解所产生的度量具有奇异性。这导致罗森布拉特过程的吉尔萨诺夫型定理失效。
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Parameter estimation and singularity of laws on the path space for SDEs driven by Rosenblatt processes
In this paper, we study parameter identification for solutions to (possibly non-linear) SDEs driven by additive Rosenblatt process and singularity of the induced laws on the path space. We propose a joint estimator for the drift parameter, diffusion intensity, and Hurst index that can be computed from discrete-time observations with a bounded time horizon and we prove its strong consistency under in-fill asymptotics with a fixed time horizon. As a consequence of this strong consistency, singularity of measures generated by the solutions with different drifts is shown. This results in the invalidity of a Girsanov-type theorem for Rosenblatt processes.
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来源期刊
Stochastic Processes and their Applications
Stochastic Processes and their Applications 数学-统计学与概率论
CiteScore
2.90
自引率
7.10%
发文量
180
审稿时长
23.6 weeks
期刊介绍: Stochastic Processes and their Applications publishes papers on the theory and applications of stochastic processes. It is concerned with concepts and techniques, and is oriented towards a broad spectrum of mathematical, scientific and engineering interests. Characterization, structural properties, inference and control of stochastic processes are covered. The journal is exacting and scholarly in its standards. Every effort is made to promote innovation, vitality, and communication between disciplines. All papers are refereed.
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