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In this paper, we derive higher order Edgeworth expansions for the finite sample distributions of the subsampling-based t-statistic and the Wald statistic in the Gaussian location model under the so-called fixed-smoothing paradigm. In…

Statistics Theory · Mathematics 2013-09-11 Xianyang Zhang , Xiaofeng Shao

We consider a class of dissipative stochastic differential equations (SDE's) with time-periodic coefficients in finite dimension, and the response of time-asymptotic probability measures induced by such SDE's to sufficiently regular, small…

Probability · Mathematics 2022-01-04 Michal Branicki , Kenneth Uda

We study using large deviation theory the fluctuations of time-integrated functionals or observables of the unbiased random walk evolving on Erd\"os-R\'enyi random graphs, and construct a modified, biased random walk that explains how these…

Statistical Mechanics · Physics 2019-03-06 Francesco Coghi , Jules Morand , Hugo Touchette

A statistical hypothesis test for long range dependence (LRD) in functional time series in manifolds has been formulated in Ruiz-Medina and Crujeiras (2025) in the spectral domain for fully observed functional data. The asymptotic Gaussian…

Statistics Theory · Mathematics 2025-11-04 M. D. Ruiz-Medina , R. M. Crujeiras

We present a comprehensive, nonperturbative analytical method to investigate the dynamics of time-dependent oscillating scalar field configurations. The method is applied to oscillons in a double well Klein-Gordon model in two and three…

High Energy Physics - Theory · Physics 2010-01-11 Marcelo Gleiser , David Sicilia

Nonstationary Gaussian processes (GPs) are essential for modeling complex, locally heterogeneous spatial data. A common modeling approach is the spatial deformation method that warps the domain to recover isotropy. However, this static…

Machine Learning · Computer Science 2026-05-01 Minghao Gu , Weizhi Lin , Qiang Huang

We consider multivariate copula-based stationary time-series under Gaussian subordination. Observed time series are subordinated to long-range dependent Gaussian processes and characterized by arbitrary marginal copula distributions. First…

Statistics Theory · Mathematics 2018-03-16 Yusufu Simayi

In this work we study configurations in one-dimensional scalar field theory, which are time-dependent, localized in space and extremely long-lived called oscillons. It is investigated how the action of changing the minimum value of the…

High Energy Physics - Theory · Physics 2016-02-03 R. A. C. Correa , A. de Souza Dutra

In this paper, we examine the long-run distribution of stochastic gradient descent (SGD) in general, non-convex problems. Specifically, we seek to understand which regions of the problem's state space are more likely to be visited by SGD,…

Optimization and Control · Mathematics 2026-05-19 Waïss Azizian , Franck Iutzeler , Jérôme Malick , Panayotis Mertikopoulos

Let $X(t), t\in \mathcal{T}$ be a centered Gaussian random field with variance function $\sigma^2(\cdot)$ that attains its maximum at the unique point $t_0\in \mathcal{T}$, and let $M(\mathcal{T}):=\sup_{t\in \mathcal{T}} X(t)$. For…

Probability · Mathematics 2016-05-31 Krzyztof Dębicki , Enkelejd Hashorva , Peng Liu

We study the short-time asymptotical behavior of stochastic flows on \mathbb{R} in the \sup-norm. The results are stated in terms of a Gaussian process associated with the covariation of the flow. In case the Gaussian process has a…

Probability · Mathematics 2010-10-27 Alexander Shamov

We study the asymptotic properties of the trajectories of a discrete-time random dynamical system in an infinite-dimensional Hilbert space. Under some natural assumptions on the model, we establish a multiplica-tive ergodic theorem with an…

Analysis of PDEs · Mathematics 2020-01-22 Davit Martirosyan , Vahagn Nersesyan

We prove empirical central limit theorems for the distribution of levels of various random fields defined on high-dimensional discrete structures as the dimension of the structure goes to $\infty$. The random fields considered include costs…

Probability · Mathematics 2012-03-08 Zakhar Kabluchko

This work deals with the stationary analysis of two-dimensional partially homogeneous nearest-neighbour random walks. Such type of random walks in the quarter plane are characterized by the fact that the one-step transition probabilities…

Networking and Internet Architecture · Computer Science 2019-07-11 Ioannis Dimitriou

We tackle the modeling of threshold exceedances in asymptotically independent stochastic processes by constructions based on Laplace random fields. These are defined as Gaussian random fields scaled with a stochastic variable following an…

Methodology · Statistics 2016-03-09 Thomas Opitz

With the rapid advances of data acquisition techniques, spatio-temporal data are becoming increasingly abundant in a diverse array of disciplines. Here we develop spatio-temporal regression methodology for analyzing large amounts of…

Methodology · Statistics 2021-12-01 Ting Fung Ma , Fangfang Wang , Jun Zhu , Anthony R. Ives , Katarzyna E. Lewińska

When a random field $(X_t, \ t\in {\mathbb R}^2)$ is thresholded on a given level $u$, the excursion set is given by its indicator $~1_{[u, \infty)}(X_t)$. The purpose of this work is to study functionals (as established in stochastic…

Probability · Mathematics 2014-10-30 Marie Kratz , Werner Nagel

We present results of micron - resolution measurements of the ground motions in large particle accelerators over the range of spatial scales L from several meters to tens of km and time intervals T from minutes to several years and show…

Accelerator Physics · Physics 2015-06-04 Vladimir Shiltsev

In this article, we study linearly edge-reinforced random walk on general multi-level ladders for large initial edge weights. For infinite ladders, we show that the process can be represented as a random walk in a random environment, given…

Probability · Mathematics 2007-05-23 Franz Merkl , Silke W. W. Rolles

This paper presents a solution for persistent monitoring of real-world stochastic phenomena, where the underlying covariance structure changes sharply across time, using a small number of mobile robot sensors. We propose an adaptive…

Robotics · Computer Science 2018-04-30 Sahil Garg , Nora Ayanian
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