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Extremes of a type of locally stationary Gaussian random fields with applications to Shepp statistics

Authors :
Tan, Zhongquan
Zheng, Shengchao
Publication Year :
2019

Abstract

Let $\{Z(\tau,s), (\tau,s)\in [a,b]\times[0,T]\}$ with some positive constants $a,b,T$ be a centered Gaussian random field with variance function $\sigma^{2}(\tau,s)$ satisfying $\sigma^{2}(\tau,s)=\sigma^{2}(\tau)$. We firstly derive the exact tail asymptotics for the maximum $M_{H}(T)=\max_{(\tau,s)\in[a,b]\times[0,T]}Z(\tau,s)/\sigma(\tau)$ up crossing some level $u$ with any fixed $0<a<b<\infty$ and $T>0$; and we further derive the extreme limit law for $M_{H}(T)$. As applications of the main results, we derive the exact tail asymptotics and the extreme limit law for Shepp statistics with stationary Gaussian process, fractional Brownian motion and Gaussian integrated process as input.<br />Comment: 15 pages,0 figures

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.1910.03794
Document Type :
Working Paper