LEAST SQUARES TYPE ESTIMATION FOR DISCRETELY OBSERVED NON-ERGODIC GAUSSIAN ORNSTEIN-UHLENBECK PROCES

• 作 者: Khalifa ES-SEBAIY Fares ALAZEM
• 机 构: DepartmentofMathematics
• 出 处: 数学物理学报:B辑英文版
• 发表日期: 2019年4期
• 关键词: Drift parameter ESTIMATION non-ergodic GAUSSIAN ORNSTEIN-UHLENBECK process discr
• 基金项目: supported and funded by Kuwait University, Research Project No. SM01/16.

In this article, we consider the drift parameter estimation problem for the nonergodic Ornstein-Uhlenbeck process defined as dXt = OXtdt + dGt, i > 0 with an unknown parameter θ> 0, where G is a Gaussian process. We assume that the process {xt,t≥ 0}