English

Berry-Esseen bounds of second moment estimators for Gaussian processes observed at high frequency

Statistics Theory 2021-02-10 v1 Probability Statistics Theory

Abstract

Let Z:={Zt,t0}Z:=\{Z_t,t\geq0\} be a stationary Gaussian process. We study two estimators of E[Z02]\mathbb{E}[Z_0^2], namely f^T(Z):=1T0TZt2dt\widehat{f}_T(Z):= \frac{1}{T} \int_{0}^{T} Z_{t}^{2}dt, and f~n(Z):=1ni=1nZti2\widetilde{f}_n(Z) :=\frac{1}{n} \sum_{i =1}^{n} Z_{t_{i}}^{2}, where ti=iΔn t_{i} = i \Delta_{n}, i=0,1,,n i=0,1,\ldots, n , Δn0\Delta_{n}\rightarrow 0 and Tn:=nΔn T_{n} := n \Delta_{n}\rightarrow \infty. We prove that the two estimators are strongly consistent and establish Berry-Esseen bounds for a central limit theorem involving f^T(Z)\widehat{f}_T(Z) and f~n(Z)\widetilde{f}_n(Z). We apply these results to asymptotically stationary Gaussian processes and estimate the drift parameter for Gaussian Ornstein-Uhlenbeck processes.

Keywords

Cite

@article{arxiv.2102.04810,
  title  = {Berry-Esseen bounds of second moment estimators for Gaussian processes observed at high frequency},
  author = {Soukaina Douissi and Khalifa Es-Sebaiy and George Kerchev and Ivan Nourdin},
  journal= {arXiv preprint arXiv:2102.04810},
  year   = {2021}
}