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Motivated by the problem of testing for the existence of a signal of known parametric structure and unknown ``location'' (as explained below) against a noisy background, we obtain for the maximum of a centered, smooth random field an…

Statistics Theory · Mathematics 2008-06-27 Yuval Nardi , David O. Siegmund , Benjamin Yakir

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

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

We derive a scale-free bound on the density of the maximum of a centered Gaussian vector. The basic bound is non-uniform, depends logarithmically on the dimension, and allows any covariance matrix. When the largest marginal variance is…

Statistics Theory · Mathematics 2026-05-29 Suhas Vijaykumar

We show that the centered maximum of a sequence of log-correlated Gaussian fields in any dimension converges in distribution, under the assumption that the covariances of the fields converge in a suitable sense. We identify the limit as a…

Probability · Mathematics 2024-02-23 Jian Ding , Rishideep Roy , Ofer Zeitouni

We obtain a number of results regarding the distribution of values of a quadratic function f on the set of nxn permutation matrices (identified with the symmetric group S_n) around its optimum (minimum or maximum). In particular, we…

Combinatorics · Mathematics 2007-05-23 Alexander Barvinok , Tamon Stephen

We study the distribution of the maximum of a large class of Gaussian fields indexed by a box $V_N\subset Z^d$ and possessing logarithmic correlations up to local defects that are sufficiently rare. Under appropriate assumptions that…

Probability · Mathematics 2022-05-17 Florian Schweiger , Ofer Zeitouni

Gaussian random fields on Euclidean spaces whose variances reach their maximum values at unique points are considered. Exact asymptotic behaviors of probabilities of large absolute maximum of theirs trajectories have been evaluated using…

Probability · Mathematics 2019-04-12 Sergey G. Kobelkov , Vladimir I. Piterbarg

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

Suppose that the edges of a complete graph are assigned weights independently at random and we ask for the weight of the minimal-weight spanning tree, or perfect matching, or Hamiltonian cycle. For these and several other common…

Combinatorics · Mathematics 2025-01-28 Yun Cheng , Yixue Liu , Tomasz Tkocz , Albert Xu

This paper derives a new strong Gaussian approximation bound for the sum of independent random vectors. The approach relies on the optimal transport theory and yields \textit{explicit} dependence on the dimension size $p$ and the sample…

Statistics Theory · Mathematics 2021-09-06 Nazar Buzun , Nikolay Shvetsov , Dmitry V. Dylov

In this article we give a general criterion for some dependent Gaussian models to belong to maximal domain of attraction of Gumbel, following an application of the Stein-Chen method studied in Arratia et al(1989). We also show the…

Probability · Mathematics 2016-11-03 Alberto Chiarini , Alessandra Cipriani , Rajat Subhra Hazra

Let $x_1 < \dots < x_n$ and $y_1 < \dots < y_n$, $n \in \mathbb N$, be real numbers. We show by an example that the assignment problem $$ \max_{\sigma \in S_n} F_\sigma(x,y) := \frac12 \sum_{i,k=1}^n |x_i - x_k|^\alpha \, |y_{\sigma(i)} -…

Numerical Analysis · Mathematics 2022-05-19 Robert Beinert , Cosmas Heiss , Gabriele Steidl

Given a Gaussian Markov random field, we consider the problem of selecting a subset of variables to observe which minimizes the total expected squared prediction error of the unobserved variables. We first show that finding an exact…

Machine Learning · Computer Science 2012-09-27 Satyaki Mahalanabis , Daniel Stefankovic

We discuss the optimal matching solution for both the assignment problem and the matching problem in one dimension for a large class of convex cost functions. We consider the problem in a compact set with the topology both of the interval…

Disordered Systems and Neural Networks · Physics 2017-10-11 Sergio Caracciolo , Matteo D'Achille , Gabriele Sicuro

The asymptotic results that underlie applications of extreme random fields often assume that the variables are located on a regular discrete grid, identified with $\mathbb{Z}^2$, and that they satisfy stationarity and isotropy conditions.…

Probability · Mathematics 2015-09-03 Helena Ferreira , Luísa Pereira , Ana Paula Martins

We continue the study of the maximum of the scale-inhomogeneous discrete Gaussian free field in dimension two. In this paper, we consider the regime of weak correlations and prove the convergence in law of the centred maximum to a randomly…

Probability · Mathematics 2020-10-05 Maximilian Fels , Lisa Hartung

We study asymptotic probabilities of attaining the maximum in heterogeneous Gaussian samples. In the two-group setting, the first sample has variance $1$ and size $n_1$, while the second has variance $\sigma^2>1$ and size $n_2$. We…

Probability · Mathematics 2026-05-21 Chunxu Zhang , Baiqi Miao , Tiantian Mao

Let $A$ be a real skew-symmetric Gaussian random matrix whose upper triangular elements are independently distributed according to the standard normal distribution. We provide the distribution of the largest singular value $\sigma_1$ of…

Statistics Theory · Mathematics 2010-03-16 Satoshi Kuriki

A local convergence rate is established for a Gauss orthogonal collocation method applied to optimal control problems with control constraints. If the Hamiltonian possesses a strong convexity property, then the theory yields convergence for…

Numerical Analysis · Mathematics 2018-09-17 William W. Hager , Jun Liu , Subhashree Mohapatra , Anil V. Rao , Xiang-Sheng Wang
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