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The theory of finite-size scaling explains how the singular behavior of thermodynamic quantities in the critical point of a phase transition emerges when the size of the system becomes infinite. Usually, this theory is presented in a…

Statistical Mechanics · Physics 2017-02-08 Alvaro Corral , Rosalba Garcia-Millan , Francesc Font-Clos

This work presents a family of parsimonious Gaussian process models which allow to build, from a finite sample, a model-based classifier in an infinite dimensional space. The proposed parsimonious models are obtained by constraining the…

Methodology · Statistics 2012-06-18 Charles Bouveyron , Stéphane Girard , Mathieu Fauvel

Any limiting point process for the time normalized exceedances of high levels by a stationary sequence is necessarily compound Poisson under appropriate long range dependence conditions. Typically exceedances appear in clusters. The…

Applications · Statistics 2009-03-03 Christian Y. Robert

We study the large deviation behaviour of the trajectories of empirical distributions of independent copies of time-homogeneous Feller processes on locally compact metric spaces. Under the condition that we can find a suitable core for the…

Functional Analysis · Mathematics 2018-03-13 Richard C. Kraaij

In this paper, we consider the discrete membrane model in four dimensions. We confirm the existence of the scaling limit of the intermediate (i.e., a multiple of the expected maximum) level-sets of the model, and show that it is equal in…

Probability · Mathematics 2025-09-22 Xinyi Li , Runsheng Liu

The infinitely-many-neutral-alleles model has recently been extended to a class of diffusion processes associated with Gibbs partitions of two-parameter Poisson-Dirichlet type. This paper introduces a family of infinite-dimensional…

Probability · Mathematics 2013-02-15 Matteo Ruggiero , Stephen G. Walker , Stefano Favaro

While most Bayesian nonparametric models in machine learning have focused on the Dirichlet process, the beta process, or their variants, the gamma process has recently emerged as a useful nonparametric prior in its own right. Current…

Machine Learning · Statistics 2017-04-17 Anirban Roychowdhury , Brian Kulis

The conditional extremes framework allows for event-based stochastic modeling of dependent extremes, and has recently been extended to spatial and spatio-temporal settings. After standardizing the marginal distributions and applying an…

Methodology · Statistics 2024-03-26 Emma S. Simpson , Thomas Opitz , Jennifer L. Wadsworth

A particle-in-cell algorithm is derived with a canonical Poisson structure in the formalism of finite element exterior calculus. The resulting method belongs to the class of gauge-compatible splitting algorithms, which exactly preserve…

Plasma Physics · Physics 2022-05-05 Alexander S. Glasser , Hong Qin

We study the extreme point process associated to the off-diagonal components in the matrix representation of the Gaussian $\beta$-Ensemble and prove its convergence to Poisson point process as $n\to +\infty$ when the inverse temperature…

Probability · Mathematics 2019-03-07 Cambyse Pakzad

Some examples of translation invariant site percolation processes on the $\Z^2$ lattice are constructed, the most far-reaching example being one that satisfies uniform finite energy (meaning that the probability that a site is open given…

Probability · Mathematics 2010-11-15 Olle Hägström , Péter Mester

This paper studies the joint tail asymptotics of extrema of the multi-dimensional Gaussian process over random intervals defined as $$ P(u):=\mathbb{P}\left\{\cap_{i=1}^n \left(\sup_{t\in[0,\mathcal{T}_i]} ( X_{i}(t) +c_i t )>a_i u…

Probability · Mathematics 2020-09-28 Lanpeng Ji , Xiaofan Peng

In this paper, we propose a new comparison tool for spatial homogeneity of point processes, based on the joint examination of void probabilities and factorial moment measures. We prove that determinantal and permanental processes, as well…

Probability · Mathematics 2014-04-23 Bartlomiej Blaszczyszyn , D. Yogeshwaran

Consider the mutually catalytic branching process with finite branching rate $\gamma$. We show that as $\gamma\to\infty$, this process converges in finite-dimensional distributions (in time) to a certain discontinuous process. We give…

Probability · Mathematics 2010-10-20 Achim Klenke , Leonid Mytnik

We consider a stationary stochastic volatility field $Y_vZ_v$ with $v\in\mathbb{Z}^d$, where $Z$ is regularly varying and $Y$ has lighter tails and is independent of $Z$. We make - relative to existing literature - very general assumptions…

Probability · Mathematics 2023-01-25 Mads Stehr , Anders Rønn-Nielsen

We study asymptotic properties of supercritical Galton-Watson (GW) branching processes in the asymptotic where the mean of the offspring distribution approaches 1 from above. We show that the population-size distribution of the GW branching…

Probability · Mathematics 2026-03-05 Kyoya Uemura , Tomoyuki Obuch , Toshiyuki Tanaka

Inhomogeneous environments are rather ubiquitous in nature, often implying anomalies resulting in deviation from Gaussianity of diffusion processes. While sub- and superdiffusion are usually due to conversing environmental features…

Statistical Mechanics · Physics 2023-05-23 Attilio L. Stella , Aleksei Chechkin , Gianluca Teza

We prove that the scaling limits of spin fluctuations in four-dimensional Ising-type models with nearest-neighbor ferromagnetic interaction at or near the critical point are Gaussian. A similar statement is proven for the $\lambda \phi^4$…

Mathematical Physics · Physics 2022-01-25 Michael Aizenman , Hugo Duminil-Copin

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

In this paper, we propose a data based transformation for infinite-dimensional Gaussian processes and derive its limit theorem. For a classification problem, this transformation induces complete separation among the associated Gaussian…

Statistics Theory · Mathematics 2022-03-25 Juan A. Cuesta-Albertos , Subhajit Dutta