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On Piterbarg Max-discretisation Theorem for Multivariate Stationary Gaussian Processes

Probability 2014-12-12 v1

Abstract

Let {X(t),t0}\{X(t), t\geq0\} be a stationary Gaussian process with zero-mean and unit variance. A deep result derived in Piterbarg (2004), which we refer to as Piterbarg's max-discretisation theorem gives the joint asymptotic behaviour (TT\to \infty) of the continuous time maximum M(T)=maxt[0,T]X(t),M(T)=\max_{t\in [0,T]} X(t), and the maximum Mδ(T)=maxtR(δ)X(t),M^{\delta}(T)=\max_{t\in \mathfrak{R}(\delta)}X(t), with R(δ)[0,T]\mathfrak{R}(\delta) \subset [0,T] a uniform grid of points of distance δ=δ(T)\delta=\delta(T). Under some asymptotic restrictions on the correlation function Piterbarg's max-discretisation theorem shows that for the limit result it is important to know the speed δ(T)\delta(T) approaches 0 as TT\to \infty. The present contribution derives the aforementioned theorem for multivariate stationary Gaussian processes.

Keywords

Cite

@article{arxiv.1405.2457,
  title  = {On Piterbarg Max-discretisation Theorem for Multivariate Stationary Gaussian Processes},
  author = {Z. Tan and E. Hashorva},
  journal= {arXiv preprint arXiv:1405.2457},
  year   = {2014}
}
R2 v1 2026-06-22T04:10:48.878Z