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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 obtain necessary and sufficient conditions for the regular variation of the variance of partial sums of functionals of discrete and continuous-time stationary Markov processes with normal transition operators. We also construct a class…

Probability · Mathematics 2014-05-13 George Deligiannidis , Magda Peligrad , Sergey Utev

We consider the Fleming--Viot particle system associated with a continuous-time Markov chain in a finite space. Assuming irreducibility, it is known that the particle system possesses a unique stationary distribution, under which its…

Probability · Mathematics 2019-04-22 Tony Lelievre , Loucas Pillaud-Vivien , Julien Reygner

The aim of this paper is to compare various criteria leading to the central limit theorem and the weak invariance principle. These criteria are the martingale-coboundary decomposition developed by Gordin in Dokl. Akad. Nauk SSSR 188 (1969),…

Probability · Mathematics 2008-12-18 Olivier Durieu , Dalibor Volný

In this paper we study the almost sure central limit theorem started from a point for additive functionals of a stationary and ergodic Markov chain via a martingale approximation in the almost sure sense. As a consequence we derive the…

Probability · Mathematics 2009-11-26 Christophe Cuny , Magda Peligrad

In this paper, we establish a central limit theorem for a large class of general supercritical superprocesses with immigration with spatially dependent branching mechanisms satisfying a second moment condition. This central limit theorem…

Probability · Mathematics 2016-12-13 Li Wang

In this paper we study supercritical super-OU processes with general branching mechanisms satisfying a second moment condition. We establish central limit theorems for the super-OU processes. In the small and crtical branching rate cases,…

Probability · Mathematics 2013-02-07 Yan-Xia Ren , Renming Song , Rui Zhang

The goal of this paper is to highlight the almost sure central limit theorem for martingales to the control community and to show the usefulness of this result for the system identification of controllable ARX(p,q) process in adaptive…

Optimization and Control · Mathematics 2018-11-26 Bernard Bercu , Victor Vazquez

We present a central limit theorem for stationary random fields that are short-range dependent and asymptotically independent. As an application, we present a central limit theorem for an infinite family of interacting It\^o-type diffusion…

Probability · Mathematics 2021-10-19 Le Chen , Davar Khoshnevisan , David Nualart , Fei Pu

We present a general central limit theorem with simple, easy-to-check covariance-based sufficient conditions for triangular arrays of random vectors when all variables could be interdependent. The result is constructed from Stein's method,…

In this paper, we establish some functional central limit theorems for a large class of general supercritical superprocesses with spatially dependent branching mechanisms satisfying a second moment condition. In the particular case when the…

Probability · Mathematics 2014-10-08 Yan-Xia Ren , Renming Song , Rui Zhang

In this paper, we investigate annealed and quenched limit theorems for random expanding dynamical systems. Making use of functional analytic techniques and more probabilistic arguments with martingales, we prove annealed versions of a…

Dynamical Systems · Mathematics 2014-07-18 Romain Aimino , Matthew Nicol , Sandro Vaienti

Let $(U_n(t))_{t\in\R^d}$ be the empirical process associated to an $\R^d$-valued stationary process $(X_i)_{i\ge 0}$. We give general conditions, which only involve processes $(f(X_i))_{i\ge 0}$ for a restricted class of functions $f$,…

Probability · Mathematics 2012-10-02 Olivier Durieu , Marco Tusche

For a L\'evy basis $L$ on $\mathbb{R}^d$ and a suitable kernel function $f:\mathbb{R}^d \to \mathbb{R}$, consider the continuous spatial moving average field $X=(X_t)_{t\in \mathbb{R}^d}$ defined by $X_t = \int_{\mathbb{R}^d} f(t-s) \,…

Probability · Mathematics 2021-08-02 David Berger

The work [8] established memory loss in the time-dependent (non-random) case of uniformly expanding maps of the interval. Here we find conditions under which we have convergence to the normal distribution of the appropriately scaled…

Dynamical Systems · Mathematics 2016-03-25 Peter Nandori , Domokos Szasz , Tamas Varju

This article presents a weak law of large numbers and a central limit theorem for the scaled realised covariation of a bivariate Brownian semistationary process. The novelty of our results lies in the fact that we derive the suitable…

Probability · Mathematics 2017-07-27 Andrea Granelli , Almut E. D. Veraart

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

Nourdin et al. [9] established the following universality result: if a sequence of off-diagonal homogeneous polynomial forms in i.i.d. standard normal random variables converges in distribution to a normal, then the convergence also holds…

Probability · Mathematics 2015-05-15 Shuyang Bai , Murad S. Taqqu

We prove the central limit theorem (CLT) for a sequence of independent zero-mean random variables $\xi_j$, perturbed by predictable multiplicative factors $\lambda_j$ with values in intervals $[\underline\lambda_j,\overline\lambda_j]$. It…

Probability · Mathematics 2015-08-31 Dmitry B. Rokhlin

In this paper, we investigate the functional central limit theorem for stochastic processes associated to partial sums of additive functionals of reversible Markov chains with general spate space, under the normalization standard deviation…

Probability · Mathematics 2022-08-02 Magda Peligrad , Sergey Utev
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