Journal of Applied Probability

Extremes of homogeneous Gaussian random fields

Krzysztof Dębicki, Enkelejd Hashorva, and Natalia Soja-Kukieła

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Let {X(s, t): s, t ≥ 0} be a centred homogeneous Gaussian field with almost surely continuous sample paths and correlation function r(s, t) = cov(X(s, t), X(0, 0)) such that r(s, t) = 1 - |s|α1 - |t|α2 + o(|s|α1 + |t|α2), s, t → 0, with α1, α2 ∈ (0, 2], and r(s, t) < 1 for (s, t) ≠ (0, 0). In this contribution we derive an asymptotic expansion (as u → ∞) of P(sup(sn1(u),tn2(u)) ∈[0,x]∙[0,y]X(s, t) ≤ u), where n1(u)n2(u) = u2/α1+2/α2Ψ(u), which holds uniformly for (x, y) ∈ [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 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).

Article information

J. Appl. Probab. Volume 52, Number 1 (2015), 55-67.

First available in Project Euclid: 17 April 2015

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Mathematical Reviews number (MathSciNet)

Zentralblatt MATH identifier

Primary: 60G15: Gaussian processes
Secondary: 60G70: Extreme value theory; extremal processes

Gaussian random field supremum tail asymptoticy extremal index Berman condition strong dependence


Dębicki, Krzysztof; Hashorva, Enkelejd; Soja-Kukieła, Natalia. Extremes of homogeneous Gaussian random fields. J. Appl. Probab. 52 (2015), no. 1, 55--67. doi:10.1239/jap/1429282606.

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