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Related papers: Extremes of Vector-Valued Gaussian Processes

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The asymptotic analysis of high exceedance probabilities for Gaussian processes and fields has been a blooming research area since J. Pickands introduced the now-standard techniques in the late 60's. The \textit{vector-valued} processes,…

Probability · Mathematics 2024-01-12 Ievlev Pavel , Kriukov Nikolai

Let $\{X_i(t),t\ge0\}, 1\le i\le n$ be mutually independent centered Gaussian processes with almost surely continuous sample paths. We derive the exact asymptotics of $$ P\left(\exists_{t \in [0,T]} \forall_{i=1 ... n} X_i(t)> u \right) $$…

Probability · Mathematics 2015-05-26 Krzysztof Dȩbicki , Enkelejd Hashorva , Lanpeng Ji , Kamil Tabiś

Gaussian random processes which variances reach theirs maximum values at unique points are considered. Exact asymptotic behaviors of probabilities of large absolute maximums of theirs trajectories have been evaluated using Double Sum Method…

Probability · Mathematics 2019-01-29 E. Hashorva , S. Kobelkov , V. I. Piterbarg

This paper investigates extreme value theory for processes obtained by applying transformations to stationary Gaussian processes, also called subordinated Gaussian processes. The main contributions are as follows. First, we refine the…

Probability · Mathematics 2026-05-29 Shuyang Bai , Marie-Christine Duker

This paper gives a new representation of Pickands' constants, which arise in the study of extremes for a variety of Gaussian processes. Using this representation, we resolve the long-standing problem of devising a reliable algorithm for…

Probability · Mathematics 2015-03-13 A. B. Dieker , B. Yakir

Starting from the notion of multivariate fractional Brownian Motion introduced in [F. Lavancier, A. Philippe, and D. Surgailis. Covariance function of vector self-similar processes. Statistics & Probability Letters, 2009] we define a…

Probability · Mathematics 2025-09-16 Ranieri Dugo , Giacomo Giorgio , Paolo Pigato

We study rates of convergence in central limit theorems for the partial sum of squares of general Gaussian sequences, using tools from analysis on Wiener space. No assumption of stationarity, asymptotically or otherwise, is made. The main…

Probability · Mathematics 2017-06-09 Soukaina Douissi , Khalifa Es-Sebaiy , Frederi G. Viens

Let $X_{i,n},n\in \mathbb{N},1\leq i\leq n$, be a triangular array of independent $\mathbb{R}^d$-valued Gaussian random vectors with correlation matrices $\Sigma_{i,n}$. We give necessary conditions under which the row-wise maxima converge…

Probability · Mathematics 2015-04-08 Sebastian Engelke , Zakhar Kabluchko , Martin Schlather

Let $\{X_i(t),t\ge0\}, 1\le i\le n$ be independent copies of a stationary process $\{X(t), t\ge0\}$. For given positive constants $u,T$, define the set of $r$th conjunctions $ C_{r,T,u}:= \{t\in [0,T]: X_{r:n}(t) > u\}$ with $X_{r:n}(t)$…

Probability · Mathematics 2014-08-07 Krzysztof Debicki , Enkelejd Hashorva , Lanpeng Ji , Chengxiu Ling

This contribution establishes exact tail asymptotics of $\sup_{(s,t)\in\mathbf{E}}$ $X(s,t)$ for a large class of nonhomogeneous Gaussian random fields $X$ on a bounded convex set $\mathbf{E}\subset\mathbb{R}^2$, with variance function that…

Probability · Mathematics 2016-03-16 Krzysztof Dȩbicki , Enkelejd Hashorva , Lanpeng Ji

The $q$-Ornstein-Uhlenbeck processes, $q\in(-1,1)$, are a family of stationary Markov processes that converge weakly to the standard Ornstein-Uhlenbeck process as $q$ tends to 1. It has been noticed recently that in terms of path…

Probability · Mathematics 2017-10-27 Yizao Wang

Pickands constants play a crucial role in the asymptotic theory of Gaussian processes. They are commonly defined as the limits of a sequence of expectations involving fractional Brownian motions and, as such, their exact value is often…

Probability · Mathematics 2016-02-05 Krzysztof Dębicki , Sebastian Engelke , Enkelejd Hashorva

Let $X(t)=(X_1(t), \dots, X_n(t)), t\in \mathcal{T}\subset \mathbb{R} $ be a centered vector-valued Gaussian process with independent components and continuous trajectories, and $h(t)=(h_1(t),\dots, h_n(t)), t\in \mathcal{T} $ be a…

Probability · Mathematics 2018-01-09 Long Bai , Krzysztof Debicki , Peng Liu

We consider the persistence probability, the occupation-time distribution and the distribution of the number of zero crossings for discrete or (equivalently) discretely sampled Gaussian Stationary Processes (GSPs) of zero mean. We first…

Statistical Mechanics · Physics 2009-11-10 George M. C. A. Ehrhardt , Satya N. Majumdar , Alan J. Bray

This paper considers extreme values attained by a centered, multidimensional Gaussian process $X(t)= (X_1(t),\ldots,X_n(t))$ minus drift $d(t)=(d_1(t),\ldots,d_n(t))$, on an arbitrary set $T$. Under mild regularity conditions, we establish…

Probability · Mathematics 2015-05-22 Krzysztof Dębicki , Kamil Marcin Kosiński , Michel Mandjes , Tomasz Rolski

Statistical modeling of multivariate and spatial extreme events has attracted broad attention in various areas of science. Max-stable distributions and processes are the natural class of models for this purpose, and many parametric families…

Methodology · Statistics 2017-08-09 Clement Dombry , Sebastian Engelke , Marco Oesting

Let $\mathbf{X}=\{X_{n}\}_{n\geq 1}$ be a sequence of stationary Gaussian variables and suppose that only some of the random variables from $\mathbf{X}$ can be observed. In this paper, by studying the limiting properties of multidimensional…

Probability · Mathematics 2024-06-06 Yuan Fang , Zhongquan Tan

In this paper, we consider the distribution of the supremum of non-stationary Gaussian processes, and present a new theoretical result on the asymptotic behaviour of this distribution. Unlike previously known facts in this field, our main…

Probability · Mathematics 2020-05-25 Valentin Konakov , Vladimir Panov , Vladimir Piterbarg

The asymptotic analysis of covariance parameter estimation of Gaussian processes has been subject to intensive investigation. However, this asymptotic analysis is very scarce for non-Gaussian processes. In this paper, we study a class of…

Statistics Theory · Mathematics 2019-11-27 François Bachoc , José Bétancourt , Reinhard Furrer , Thierry Klein

We consider the Pickands process {equation*} P_{n}(s)=\log (1/s)^{-1}\log \frac{X_{n-k+1,n}-X_{n-[k/s]+1,n}}{% X_{n-[k/s]+1,n}-X_{n-[k/s^{2}]+1,n}}, {equation*} {equation*} (\frac{k}{n}\leq s^2 \leq 1), {equation*} which is a generalization…

Methodology · Statistics 2011-11-21 Gane Samb Lo , Adja Mbarka Fall
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