Cramér-type moderate deviations for statistics in the non-stationary Ornstein–Uhlenbeck process

Hui Jiang, Ning Zhang

Stochastics · 2019 · 11 citations · 25 references

Concepts

Abstract

In this paper, we study Cramér-type moderate deviations for parameter estimation in the non-stationary Ornstein–Uhlenbeck process. The main methods include the deviation inequalities for multiple Wiener-Itô integrals, as well as the asymptotic analysis techniques. For applications, we propose a test statistic which can be used to construct a rejection region in the hypothesis testing for the drift coefficient. It is shown that the probability of type II error tends to zero exponentially when using the proposed test statistic.

References

25