Estimation of all parameters in the reflected Ornstein–Uhlenbeck process from discrete observations
Yaozhong Hu and
Statistics & Probability Letters, 2021, vol. 174, issue C
Assuming that a reflected Ornstein–Uhlenbeck process is observed at discrete time instants, we propose generalized moment estimators to estimate all the drift and diffusion parameters via the celebrated ergodic theorem. With the sampling time step h>0 arbitrarily fixed, we prove the strong consistency and asymptotic normality of our estimators as the sampling size n tends to infinity. This provides a complete solution to an open problem left in Hu et al. (2015).
Keywords: Reflected Ornstein–Uhlenbeck process; Ergodic estimators; Spectral representation of transition density; Strong consistency; Asymptotic normality (search for similar items in EconPapers)
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