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arXiv 1312.2863math.PR
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齐次高斯随机场的极值

Extremes of homogeneous Gaussian random fields

Krzysztof Dębicki, Enkelejd Hashorva, Natalia Soja-Kukieła

摘要:

设$\{X(s,t):s,t\geqslant 0\}$是中心均匀高斯场,连续采样路径和相关函数$r(s,t)=Cov(X(s,t),X(0,0))$,使得\[r(s,t)=1-|s|^{α_1}-|t|^{α_2}+o(|s|^{α_1}+|t|^{α_2}), \quad s,t \to 0,\]与$α_1,α_2\in(0,2],$和$r(s,t)<1$用于$(s,t)\neq(0,0)$。在这篇文章中,我们得到了一个精确的渐近展开(作为$u\to \infty$)的$$\mathbb{P}\left(\sup_{(s n_1(u),t n_2(u))\in\left[0,x\right]\times\left[0,y\right]}X(s,t)\leqslant u\right),$$,其中$n_1(u)n_2(u)=u^{2/α_1+2/α_2}Ψ(u)$,它保持一致的$(x,y) \in [ A , B ]^2$与$ A , B $两个正常数和$Ψ$的$N(0,1)$随机变量的生存函数。我们应用我们的研究结果分析的渐近性的极端均匀高斯场在更复杂的参数集和球的随机半径。此外,我们确定了由$X(s,t)$确定的离散化随机场的极值指数。

英文摘要:

Let $\{X(s,t):s,t\geqslant 0\}$ be a centered homogeneous Gaussian field with a.s. continuous sample paths and correlation function $r(s,t)=Cov(X(s,t),X(0,0))$ such that \[r(s,t)=1-|s|^{α_1}-|t|^{α_2}+o(|s|^{α_1}+|t|^{α_2}), \quad s,t \to 0,\] with $α_1,α_2\in(0,2],$ and $r(s,t)<1$ for $(s,t)\neq(0,0)$. In this contribution we derive an exact asymptotic expansion (as $u\to \infty$) of $$\mathbb{P}\left(\sup_{(s n_1(u),t n_2(u))\in\left[0,x\right]\times\left[0,y\right]}X(s,t)\leqslant u\right),$$ where $n_1(u)n_2(u)=u^{2/α_1+2/α_2}Ψ(u)$, which holds uniformly for $(x,y) \in [ A , B ]^2$ with $ A , B $ two positive constants and $Ψ$ the survival function of an $N(0,1)$ random variable. We apply our findings to the analysis of asymptotics of extremes of homogeneous Gaussian fields over more complex parameter sets and a ball of random radius. Additionally we determine the extremal index of the discretised random field determined by $X(s,t)$.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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