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Motivated by the papers of Piterbarg (2004) and H\"{u}sler (2004), in this paper the asymptotic relation between the maximum of a continuous dependent homogeneous Gaussian random field and the maximum of this field sampled at discrete time…

Probability · Mathematics 2015-02-05 Zhongquan Tan , Kaiyong Wang

For $X_i(t), i=1,\ldots, n, t\in [0,T]$ centered Gaussian processes, the chi-square process $\sum_{i=1}^{n}X_i^2(t)$ appears naturally as limiting processes in various statistical models. In this paper, we are concerned with the exact tail…

Probability · Mathematics 2018-08-01 Long Bai

In this paper, for centered homogeneous Gaussian random fields the joint limiting distributions of normalized maxima and minima over continuous time and uniform grids are investigated. It is shown that maxima and minima are asymptotic…

Probability · Mathematics 2019-03-29 Yingyin Lu , Zuoxiang Peng

Let $\chi_n(t) = (\sum_{i=1}^n X_i^2(t))^{1/2},t\ge0$ be a chi-process with $n$ degrees of freedom where $X_i$'s are independent copies of some generic centered Gaussian process $X$. This paper derives the exact asymptotic behavior of…

Probability · Mathematics 2013-09-03 Enkelejd Hashorva , Lanpeng Ji

In this paper, we study the asymptotic relation between the maximum of acontinuous order statistics process formed by stationary Gaussian processesand the maximum of this process sampled at discrete time points. It is shown that, these two…

Probability · Mathematics 2019-10-18 Zhongquan Tan

In this paper we derive Piterbarg's max-discretisation theorem for two different grids considering centered stationary vector Gaussian processes. So far in the literature results in this direction have been derived for the joint…

Probability · Mathematics 2014-10-08 E. Hashorva , Z. Tan

In this paper, we study the asymptotic distribution of the maxima of suprema of dependent Gaussian processes with trend. For different scales of the time horizon we obtain different normalizing functions for the convergence of the maxima.…

Probability · Mathematics 2022-11-09 Lanpeng Ji , Xiaofan Peng

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

The aim of this paper is to provide models for spatial extremes in the case of stationarity. The spatial dependence at extreme levels of a stationary process is modeled using an extension of the theory of max-stable processes of de Haan and…

Statistics Theory · Mathematics 2007-06-13 Laurens de Haan , Teresa T. Pereira

Let $X(t),t\in \mathbb{R}$ be a stochastically continuous stationary max-stable process with Fr\'{e}chet marginals $\Phi_\alpha, \alpha>0$ and set $M_X(T)=\sup_{t \in [0,T]} X(t),T>0$. In the light of the seminal articles [1,2], it follows…

Probability · Mathematics 2019-12-05 Krzysztof Debicki , Enkelejd Hashorva

Let $\{X(t), t\geq0\}$ 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 ($T\to…

Probability · Mathematics 2014-12-12 Z. Tan , E. Hashorva

Let $\{X_{n}(t), t\in[0,\infty)\}, n\in\mathbb{N}$ be a sequence of centered dependent stationary Gaussian processes. The limit distribution of $\sup_{t\in[0,T(n)]}|X_{n}(t)|$ is established as $r_{n}(t)$, the correlation function of…

Probability · Mathematics 2014-12-12 Z. Tan , E. Hashorva , Z. Peng

Stationary distributions of multivariate diffusion processes have recently been proposed as probabilistic models of causal systems in statistics and machine learning. Motivated by these developments, we study stationary multivariate…

Statistics Theory · Mathematics 2024-08-02 Tobias Boege , Mathias Drton , Benjamin Hollering , Sarah Lumpp , Pratik Misra , Daniela Schkoda

Max-stable processes are natural models for spatial extremes because they provide suitable asymptotic approximations to the distribution of maxima of random fields. In the recent past, several parametric families of stationary max-stable…

Methodology · Statistics 2016-02-22 Raphael Huser , Marc G. Genton

Chi-square processes with trend appear naturally as limiting processes in various statistical models. In this paper we are concerned with the exact tail asymptotics of the supremum taken over (0; 1) of a class of locally stationary…

Probability · Mathematics 2016-07-20 Peng Liu , Lanpeng Ji

We consider the limit distribution of maxima of periodograms for stationary processes. Our method is based on $m$-dependent approximation for stationary processes and a moderate deviation result.

Statistics Theory · Mathematics 2009-08-11 Zhengyan Lin , Weidong Liu

We derive the limiting distributions of exceedances point processes of randomly scaled weakly dependent stationary Gaussian sequences under some mild asymptotic conditions. In the literature analogous results are available only for…

Probability · Mathematics 2013-10-22 Enkelejd Hashorva , Zuoxiang Peng , Zhichao Weng

For $\{X(t), t \in G_\delta\}$ a centered Gaussian process with stationary increments and a.s. sample paths on a discrete grid $G_\delta=\{0,\delta,2\delta, ...\}$, where $\delta>0$, we investigate the stationary reflected process…

Probability · Mathematics 2022-06-30 Krzysztof Dȩbicki , Grigori Jasnovidov

This paper studies the supremum of a chi-square process with trend over a threshold-dependent-time horizon. Under the assumption that the chi-square process is generated from a centered self-similar Gaussian process and the trend function…

Probability · Mathematics 2015-02-24 Peng Liu , Lanpeng Ji

Motivated by the papers of Mladenovc and Piterbarg (2006), Krajka (2011) and Pereira and Tan (2017), we study the limit properties for the maxima from nonstationary random fields subject to missing observations and obtain the weakly…

Probability · Mathematics 2023-06-27 Shengchao Zheng , Zhongquan Tan
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