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The Rotar central limit theorem is a remarkable theorem in the non-classical version since it does not use the condition of asymptotic infinitesimality for the independent individual summands, unlike the theorems named Lindeberg's and…

Probability · Mathematics 2023-09-26 Tran Loc Hung

In this paper, we derive the moderate deviation principle for stationary sequences of bounded random variables with values in a Hilbert space. The conditions obtained are expressed in terms of martingale-type conditions. The main tools are…

Probability · Mathematics 2009-01-21 Sophie Dede

This paper deals with the Gaussian and bootstrap approximations to the distribution of the max statistic in high dimensions. This statistic takes the form of the maximum over components of the sum of independent random vectors and its…

Statistics Theory · Mathematics 2022-05-31 Victor Chernozhukov , Denis Chetverikov , Kengo Kato , Yuta Koike

We prove weak laws of large numbers and central limit theorems of Lindeberg type for empirical centres of mass (empirical Fr\'echet means) of independent non-identically distributed random variables taking values in Riemannian manifolds. In…

Probability · Mathematics 2011-06-29 Wilfrid S. Kendall , Huiling Le

We study sums of a random multiplicative function; this is an example, of number-theoretic interest, of sums of products of independent random variables (chaoses). Using martingale methods, we establish a normal approximation for the sum…

Number Theory · Mathematics 2010-12-02 Adam J. Harper

Consider the stochastic differential equation in $\rr^d$ dX^{\e}_t&=b(X^{\e}_t)dt+\sqrt{\e}\sigma(X^\e_t)dB_t X^{\e}_0&=x_0,\quad x_0\in\rr^d$ where $b:\rr^d\to\rr^d$ is $C^1$ such that $<x,b(x)> \leq C(1+|x|^2)$, $\sigma:\rr^d\to…

Probability · Mathematics 2026-04-14 Yutao ma , Ran Wang , Liming Wu

We provide an abstract multivariate central limit theorem with the Lindeberg-type error bounded in terms of Lipschitz functions (Wasserstein 1-distance) or functions with bounded second or third derivatives. The result is proved by means of…

Probability · Mathematics 2019-01-03 Martin Raič

Approximations to sums of stationary and ergodic sequences by martingales are investigated. Necessary and sufficient conditions for such sums to be asymptotically normal conditionally given the past up to time 0 are obtained. It is first…

Probability · Mathematics 2007-05-23 Wei Biao Wu , Michael Woodroofe

We establish Cram\'er-type moderate deviation theorems for sums of locally dependent random variables and combinatorial central limit theorems. Under some mild exponential moment conditions, optimal error bounds and convergence ranges are…

Probability · Mathematics 2021-12-22 Song-Hao Liu , Zhuo-Song Zhang

In this paper, we obtain an explicit total variation bound in the central limit theorem for the sums of non-i.i.d. random variables. Our results show that, under suitable assumptions, Lindeberg's condition is sufficient and necessary for…

Probability · Mathematics 2025-11-25 N. T. Dung , H. T. P. Thao

In this paper, we prove a central limit theorem and estabilish a moderate deviation principle for stochastic models of incompressible second fluids. The weak convergence method inreoduced by [4] plays an important role.

Probability · Mathematics 2016-08-01 Jianliang Zhai , Tusheng Zhang , Wuting Zheng

This paper establishes a combinatorial central limit theorem for stratified randomization, which holds under a Lindeberg-type condition. The theorem allows for an arbitrary number or sizes of strata, with the sole requirement being that…

Statistics Theory · Mathematics 2024-04-16 Purevdorj Tuvaandorj

In this paper, we establish a central limit theorem and a moderate deviations for 2D stochastic primitive equations with multiplicative noise. The proof is mainly based on the weak convergence approach.

Probability · Mathematics 2017-07-10 Rangrang Zhang , Guoli Zhou

Classical works of Kac, Salem and Zygmund, and Erd\H{o}s and G\'{a}l have shown that lacunary trigonometric sums despite their dependency structure behave in various ways like sums of independent and identically distributed random…

Probability · Mathematics 2023-12-15 Joscha Prochno , Marta Strzelecka

Consider a discrete-time martingale, and let $V^2$ be its normalized quadratic variation. As $V^2$ approaches 1, and provided that some Lindeberg condition is satisfied, the distribution of the rescaled martingale approaches the Gaussian…

Probability · Mathematics 2013-03-22 Jean-Christophe Mourrat

A parametric theory of statistical inference is developed for the moderate deviation probability zone. The new approach to the proofs is based on the Taylor series expansion of the logarithm of the likelihood ratio based on the Hellinger…

Statistics Theory · Mathematics 2026-04-28 Mikhail Ermakov

Through certain appropriate constructions, we establish periodic solutions in distribution for some stochastic differential equations with infinite-dimensional Levy noise. Additionally, we obtain the corresponding periodic measures and…

Probability · Mathematics 2024-12-24 Xinying Deng , Yong Li , Xue Yang

In this paper we derive the moderate deviation principle for stationary sequences of bounded random variables under martingale-type conditions. Applications to functions of $\phi$-mixing sequences, contracting Markov chains, expanding maps…

Probability · Mathematics 2007-11-27 Jérôme Dedecker , Florence Merlevède , Magda Peligrad , Sergey Utev

We refine the classical Lindeberg-Feller central limit theorem by obtaining asymptotic bounds on the Kolmogorov distance, the Wasserstein distance, and the parametrized Prokhorov distances in terms of a Lindeberg index. We thus obtain more…

Probability · Mathematics 2016-12-26 Ben Berckmoes , Geert Molenberghs

We prove the Lindeberg--Feller central limit theorem without using characteristic functions or Taylor expansions, but instead by measuring how far a distribution is from the standard normal distribution according to the $2$-Wasserstein…

Probability · Mathematics 2024-02-28 Calvin Wooyoung Chin