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This paper deals with Poisson processes on an arbitrary measurable space. Using a direct approach, we derive formulae for moments and cumulants of a vector of multiple Wiener-It\^o integrals with respect to the compensated Poisson process.…

Probability · Mathematics 2014-07-08 Guenter Last , Mathew D. Penrose , Matthias Schulte , Christoph Thaele

In this paper, we consider the separable covariance model, which plays an important role in wireless communications and spatio-temporal statistics and describes a process where the time correlation does not depend on the spatial location…

Statistics Theory · Mathematics 2019-01-24 Huiqin Li , Yanqing Yin , Shurong Zheng

The partial transposition from quantum information theory provides a new source to distill the so-called asymptotic freeness without the assumption of classical independence between random matrices. Indeed, a recent paper [MP19] established…

Operator Algebras · Mathematics 2024-05-07 Gyunam Park , Sang-Gyun Youn

The central limit theorem is, with the strong law of large numbers, one of the two fundamental limit theorems in probability theory. Benjamin Jourdain and Alvin Tse have extended to non-linear functionals of the empirical measure of…

Probability · Mathematics 2022-04-14 Roberta Flenghi , Benjamin Jourdain

We prove a law of large numbers and functional central limit theorem for a class of multivariate Hawkes processes with time-dependent reproduction rate. We address the difficulties induced by the use of non-convolutive Volterra processes by…

Probability · Mathematics 2025-01-30 Thomas Deschatre , Pierre Gruet , Antoine Lotz

We obtain a central limit theorem for bulk counting statistics of free fermions in smooth domains of $\mathbb{R}^n$ with an explicit description of the covariance structure. This amounts to a study of the asymptotics of norms of commutators…

Spectral Theory · Mathematics 2024-05-14 Alix Deleporte , Gaultier Lambert

Ordinary differential equations obtained as limits of Markov processes appear in many settings. They may arise by scaling large systems, or by averaging rapidly fluctuating systems, or in systems involving multiple time-scales, by a…

Probability · Mathematics 2014-03-24 Hye-Won Kang , Thomas G. Kurtz , Lea Popovic

A theorem of Hegerfeldt shows that if the spectrum of the Hamiltonian is bounded from below, then the propagation speed of certain probabilities does not have an upper bound. We prove a theorem analogous to Hegerfeldt's that appertains to…

Quantum Physics · Physics 2009-11-10 S. Wickramasekara , A. Bohm

In this paper we establish spatial central limit theorems for a large class of supercritical branching Markov processes with general spatial-dependent branching mechanisms. These are generalizations of the spatial central limit theorems…

Probability · Mathematics 2013-05-06 Y. -X. Ren , R. Song , R. Zhang

Here we review and extend central limit theorems for highly chaotic but deterministic semi-dynamical discrete time systems. We then apply these results show how Brownian motion-like results are recovered, and how an Ornstein-Uhlenbeck…

Statistical Mechanics · Physics 2008-04-15 Michael C. Mackey , Marta Tyran-Kaminska

Multivariate Bessel processes $(X_{t,k})_{t\ge0}$ describe interacting particle systems of Calogero-Moser-Sutherland type and are related with $\beta$-Hermite and $\beta$-Laguerre ensembles. They depend on a root system and a multiplicity…

Probability · Mathematics 2020-09-30 Michael Voit , Jeannette H. C. Woerner

We consider nonintersecting random walks satisfying the condition that the increments have a finite moment generating function. We prove that in a certain limiting regime where the number of walks and the number of time steps grow to…

Probability · Mathematics 2011-11-09 Jinho Baik , Toufic M. Suidan

We present some applications of central limit theorems on mesoscopic scales for random matrices. When combined with the recent theory of "homogenization" for Dyson Brownian Motion, this yields the universality of quantities which depend on…

Probability · Mathematics 2019-11-28 Benjamin Landon , Philippe Sosoe

We obtain the empirical strong law of large numbers, empirical Glivenko-Cantelli theorem, central limit theorem, functional central limit theorem for various nonparametric Bayesian priors which include the Dirichlet process with general…

Statistics Theory · Mathematics 2020-11-23 Yaozhong Hu , Junxi Zhang

We investigate the behavior of Fourier transforms for a wide class of nonstationary nonlinear processes. Asymptotic central and noncentral limit theorems are established for a class of nondegenerate and degenerate weighted $V$-statistics…

Statistics Theory · Mathematics 2014-01-17 Zhou Zhou

In this paper, a connection between bi-free probability and the theory of non-commutative stochastic processes is examined. Specifically it is demonstrated that the transition operators for non-commutative stochastic processes can be…

Operator Algebras · Mathematics 2022-04-26 Paul Skoufranis

The term noncentral moderate deviations is used in the literature to mean a class of large deviation principles that, in some sense, fills the gap between the convergence in probability to a constant (governed by a reference large deviation…

Probability · Mathematics 2025-04-29 Neha Gupta , Claudio Macci

The generalized Rosenblatt process is obtained by replacing the single critical exponent characterizing the Rosenblatt process by two different exponents living in the interior of a triangular region. What happens to that generalized…

Probability · Mathematics 2016-11-10 Shuyang Bai , Murad S. Taqqu

We study central limit theorems for certain nonlinear sequences of random variables. In particular, we prove the central limit theorems for the bounded conductivity of the random resistor networks on hierarchical lattices.

Disordered Systems and Neural Networks · Physics 2007-05-23 Jung M. Woo , Jan Wehr

A famous result in renewal theory is the Central Limit Theorem for renewal processes. As in applications usually only observations from a finite time interval are available, a bound on the Kolmogorov distance to the normal distribution is…

Probability · Mathematics 2018-07-24 Gesine Reinert , Ce Yang
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