On Parameter Estimation of Hidden Ergodic Ornstein-Uhlenbeck Process
Statistics Theory
2019-02-25 v1 Statistics Theory
Abstract
We consider the problem of parameter estimation for the partially observed linear stochastic differential equation. We assume that the unobserved Ornstein-Uhlenbeck process depends on some unknown parameter and estimate the unobserved process and the unknown parameter simultaneously. We construct the two-step MLE-process for the estimator of the parameter and describe its large sample asymptotic properties, including consistency and asymptotic normality. Using the Kalman-Bucy filtering equations we construct recurrent estimators of the state and the parameter.
Cite
@article{arxiv.1902.08500,
title = {On Parameter Estimation of Hidden Ergodic Ornstein-Uhlenbeck Process},
author = {Yury A. Kutoyants},
journal= {arXiv preprint arXiv:1902.08500},
year = {2019}
}
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20 pages