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

In this article, we consider the drift parameter estimation problem for the nonergodic Ornstein-Uhlenbeck process defined as d X_t= θX_tdt + dG_t, t ≥ 0 with an unknown parameter θ 0, where G is a Gaussian process. We assume that the process {X_t, t ≥ 0} is observed at discrete time instants t_1 = ?_n, ···, t_n= n?_n, and we construct two least squares type estimators ■ and ■ for θ on the basis of the discrete observations {X_(t_i), i = 1, ···, n}as n →∞. Then, we provide sufficient conditions, based on properties of G, which ensure that ■ and ■ are strongly consistent and the sequences n?n~(1/2)(■-θ) and n?n~(1/2)(■-θ)are tight. Our approach offers an elementary proof of [11], which studied the case when G is a fractional Brownian motion with Hurst parameter H ∈(1/2, 1). As such, our results extend the recent findings by [11] to the case of general Hurst parameter H ∈(0, 1). We also apply our approach to study subfractional Ornstein-Uhlenbeck and bifractional Ornstein-Uhlenbeck processes.