Sequential estimation for nonhomogeneous Ornstein-Uhlenbeck processes

Qingpei Zang and Tao Wang

Communications in Statistics - Theory and Methods, 2019, vol. 48, issue 8, 1955-1962

Abstract: In this paper, we propose a stochastic process, which is a class of nonhomogeneous diffusion process from the perspective of the corresponding nonlinear stochastic differential equation. The parameter included in the drift term are estimated by sequential maximum likelihood methodology on the basis of continuous sampling of the process. The sequential estimators are proved to be closed, unbiased, strongly consistent, normally distributed, and optimal in the mean square sense.

Date: 2019
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DOI: 10.1080/03610926.2018.1440596

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