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On drift parameter estimation for reflected fractional Ornstein-Uhlenbeck processes

机译:分数阶Ornstein-Uhlenbeck过程的漂移参数估计

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We consider a reflected Ornstein-Uhlenbeck process X driven by a fractional Brownian motion with Hurst parameter H is an element of(0, 1/2) boolean OR (1/2, 1) . Our goal is to estimate an unknown drift parameter alpha is an element of(-infinity, infinity) on the basis of continuous observation of the state process. We establish Girsanov theorem for the process X, derive the standard maximum likelihood estimator of the drift parameter alpha, and prove its strong consistency and asymptotic normality. As an improved estimator, we obtain the explicit formulas for the sequential standard maximum likelihood estimator and its mean squared error by assuming the process is observed until a certain information reaches a specified precision level. The estimator is shown to be unbiased, uniformly normally distributed, and efficient in the mean square error sense.
机译:我们认为由Hurst参数H的分数布朗运动驱动的反射Ornstein-Uhlenbeck过程X是(0,1/2)布尔OR(1/2,1)的元素。我们的目标是在连续观察状态过程的基础上,估计未知的漂移参数alpha是(-infinity,infinity)的元素。我们为过程X建立Girsanov定理,推导漂移参数alpha的标准最大似然估计,并证明其强一致性和渐近正态性。作为一种改进的估计器,我们通过假设观察到直到某个信息达到指定的精度水平为止的过程,来获得顺序标准最大似然估计器的显式公式及其均方误差。在均方误差的意义上,估计器显示为无偏,均匀正态分布且高效。

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