Tail Asymptotics for the Extremes of Bivariate Gaussian Random Fields

preprint2015arXivOpen access

Abstract

Let {X(t)=(X1(t),X2(t))T, t∈RN}\{X(t)= (X_1(t),X_2(t))^T,\ t \in \mathbb{R}^N\} be an R2\mathbb{R}^2-valued continuous locally stationary Gaussian random field with E[X(t)]=0\mathbb{E}[X(t)]=\mathbf{0}. For any compact sets A1,A2⊂RNA_1, A_2 \subset \mathbb{R}^N, precise asymptotic behavior of the excursion probability P(max⁡s∈A1X1(s)>u, max⁡t∈A2X2(t)>u),   as  u→∞ \mathbb{P}\bigg(\max_{s\in A_1} X_1(s)>u,\, \max_{t\in A_2} X_2(t)>u\bigg),\ \ \text{ as }\ u \rightarrow \infty is investigated by applying the double sum method. The explicit results depend not only on the smoothness parameters of the coordinate fields X1X_1 and X2X_2, but also on their maximum correlation ρρ.

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