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Extremes of multidimensional stationary Gaussian random fields

Probability 2018-05-14 v3

Abstract

Let {X(t):t=(t1,t2,,td)[0,)d}\{X(\mathbf{t}):\mathbf{t}=(t_1, t_2, \ldots, t_d)\in[0,\infty)^d\} be a centered stationary Gaussian field with almost surely continuous sample paths, unit variance and correlation function rr satisfying conditions r(t)<1r(\mathbf{t})<1 for every t0\mathbf{t}\neq \mathbf{0} and r(t)=1i=1dtiαi+o(i=1dtiαi)r(\mathbf{t})=1-\sum_{i=1}^d |t_i|^{\alpha_i} + o(\sum_{i=1}^d |t_i|^{\alpha_i}), as t0\mathbf{t}\to\mathbf{0}, with constants α1,α2,,αd(0,2]\alpha_1, \alpha_2, \ldots, \alpha_d \in(0,2]. The main result of this contribution is the description of the asymptotic behaviour of P(sup{X(t):tJmx}u)P(\sup\{X(\mathbf{t}): \mathbf{t}\in\mathcal{J}^{\mathbf{x}}_{\mathbf{m}} \}\leqslant u), as uu\to\infty, for some Jordan-measurable sets Jmx\mathcal{J}^{\mathbf{x}}_{\mathbf{m}} of volume proportional to P(sup{X(t):t[0,1]d}>u)1(1+o(1))P(\sup\{X(\mathbf{t}):\mathbf{t}\in[0,1]^d\}>u)^{-1}(1+o(1)).

Keywords

Cite

@article{arxiv.1610.02888,
  title  = {Extremes of multidimensional stationary Gaussian random fields},
  author = {Natalia Soja-Kukieła},
  journal= {arXiv preprint arXiv:1610.02888},
  year   = {2018}
}
R2 v1 2026-06-22T16:16:14.144Z