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We establish a central limit theorem (CLT) for families of products of $\epsilon$-independent random variables. We utilize graphon limits to encode the evolution of independence and characterize the limiting distribution. Our framework…

Probability · Mathematics 2025-04-15 Guillaume Cébron , Patrick Oliveira Santos , Pierre Youssef

We establish central limit theorems for a large class of supercritical branching Markov processes in infinite dimension with spatially dependent and non-necessarily local branching mechanisms. This result relies on a fourth moment…

Probability · Mathematics 2025-01-31 Bertrand Cloez , Nicolás Zalduendo

In the present work we derive a Central Limit Theorem for sequences of Hilbert-valued Piecewise Deterministic Markov process models and their global fluctuations around their deterministic limit identified by the Law of Large Numbers. We…

Probability · Mathematics 2013-04-23 Martin G Riedler , Michele Thieullen

The \textit{Central Limit Theorem (CLT)} is at the heart of a great deal of applied problem-solving in statistics and data science, but the theorem is silent on an important implementation issue: \textit{how much data do you need for the…

Other Statistics · Statistics 2021-11-25 David Draper , Erdong Guo

Recent theoretical works have characterized the dynamics of wide shallow neural networks trained via gradient descent in an asymptotic mean-field limit when the width tends towards infinity. At initialization, the random sampling of the…

Probability · Mathematics 2022-03-29 Zhengdao Chen , Grant M. Rotskoff , Joan Bruna , Eric Vanden-Eijnden

In this paper, concerning SDEs with H\"older continuous drifts, which are merely dissipative at infinity, and SDEs with piecewise continuous drifts, we investigate the strong law of large numbers and the central limit theorem for underlying…

Probability · Mathematics 2024-03-12 Jianhai Bao , Jiaqing Hao

Recent work has proposed the use of a composite hypothesis Hoeffding test for statistical anomaly detection. Setting an appropriate threshold for the test given a desired false alarm probability involves approximating the false alarm…

Information Theory · Computer Science 2016-09-19 Jing Zhang , Ioannis Ch. Paschalidis

In this paper, under mild assumptions, we derive a law of large numbers, a central limit theorem with an error estimate, an almost sure invariance principle and a variant of Chernoff bound in finite-state hidden Markov models. These limit…

Information Theory · Computer Science 2012-04-13 Guangyue Han

We establish the fractional diffusion limit of the kinetic scattering equation with diffusive boundary condition in a strongly convex bounded domain $\mathcal{D}\subset\mathbb{R}^d$. According to the nature of the boundary condition, two…

Probability · Mathematics 2025-12-22 Loïc Béthencourt , Nicolas Fournier

In this paper we consider the asymptotic distributions of functionals of the sample covariance matrix and the sample mean vector obtained under the assumption that the matrix of observations has a matrix-variate location mixture of normal…

Statistics Theory · Mathematics 2023-04-19 Taras Bodnar , Stepan Mazur , Nestor Parolya

Central limit theorems play an important role in the study of statistical inference for stochastic processes. However, when the nonparametric local polynomial threshold estimator, especially local linear case, is employed to estimate the…

Probability · Mathematics 2017-02-06 Yuping Song , Hanchao Wang

We consider the existence of the integrated density of states (IDS) of the Anderson model on the Hilbert space $\ell^2(\mathbb{Z}^d)$ as analogues to the law of large numbers (LLN). In this work, we prove the analogues central limit theorem…

Mathematical Physics · Physics 2024-12-04 Dhriti Ranjan Dolai

In this paper we study the central limit theorem for additive functionals of stationary Markov chains with general state space by using a new idea involving conditioning with respect to both the past and future of the chain. Practically, we…

Probability · Mathematics 2020-05-19 Magda Peligrad

Statistical inference for non-stationary data is hindered by the failure of classical central limit theorems (CLTs), not least because there is no fixed Gaussian limit to converge to. To resolve this, we introduce relative weak convergence,…

Statistics Theory · Mathematics 2025-10-28 Nicolai Palm , Thomas Nagler

We study the convergence in distribution norms in the Central Limit Theorem for non identical distributed random variables that is $$ \varepsilon_{n}(f):={\mathbb{E}}\Big(f\Big(\frac 1{\sqrt…

Probability · Mathematics 2019-05-16 Vlad Bally , Lucia Caramellino , Guillaume Poly

We study the fluctuations of the eigenvalues of real valued large centrosymmetric random matrices via its linear eigenvalue statistic. This is essentially a central limit theorem (CLT) for sums of dependent random variables. The dependence…

Probability · Mathematics 2025-10-01 Indrajit Jana , Sunita Rani

We consider additive functionals of Markov processes in continuous time with general (metric) state spaces. We derive concentration bounds for their exponential moments and moments of finite order. Applications include diffusions,…

Probability · Mathematics 2022-02-18 Frank Redig , Florian Völlering

Using a central limit theorem for arrays of interacting quantum systems, we give analytical expressions for the density of states and the partition function at finite temperature of such a system, which are valid in the limit of infinite…

Statistical Mechanics · Physics 2009-11-10 Michael Hartmann , Guenter Mahler , Ortwin Hess

Two similar Minkowskian diffusions have been considered, on one hand by Barbachoux, Debbasch, Malik and Rivet ([BDR1], [BDR2], [BDR3], [DMR], [DR]), and on the other hand by Dunkel and H\"anggi ([DH1], [DH2]). We address here two questions,…

Probability · Mathematics 2009-11-13 Jürgen Angst , Jacques Franchi

This paper establishes limit theorems for a class of stochastic hybrid systems (continuous deterministic dynamic coupled with jump Markov processes) in the fluid limit (small jumps at high frequency), thus extending known results for jump…

Probability · Mathematics 2010-01-15 K. Pakdaman , M. Thieullen , G. Wainrib