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In this work, we study the normal approximation and almost sure central limit theorems for some functionals of an independent sequence of Rademacher random variables. In particular, we provide a new chain rule that improves the one derived…

Probability · Mathematics 2018-10-16 Guangqu Zheng

The production of molecules in a chemical reaction network is modelled as a Poisson process with a Markov-modulated arrival rate and an exponential decay rate. We analyze the distributional properties of $M$, the number of molecules, under…

Probability · Mathematics 2013-09-17 D. Anderson , J. Blom , M. Mandjes , H. Thorsdottir , K. de Turck

We prove quenched versions of a central limit theorem, a large deviations principle as well as a local central limit theorem for expanding on average cocycles. This is achieved by building an appropriate modification of the spectral method…

Dynamical Systems · Mathematics 2021-11-25 Davor Dragičević , Julien Sedro

We prove a central limit theorem for stationary multiple (random) fields of martingale differences $f\circ T_{\underline{i}}$, $\underline{i}\in \Bbb Z^d$, where $T_{\underline{i}}$ is a $\Bbb Z^d$ action. In most cases the multiple…

Probability · Mathematics 2018-03-28 Dalibor Volny

We develop a martingale approximation approach to studying the limiting behavior of quadratic forms of Markov chains. We use the technique to examine the asymptotic behavior of lag-window estimators in time series and we apply the results…

Probability · Mathematics 2011-08-16 Yves F. Atchade , Matias D. Cattaneo

The goal of this paper is to describe conditions which guarantee a central limit theorem for random variables, which distributions are controled by hidden Markov chains. We proved that when a Markov chain is ergodic and random variables…

Statistics Theory · Mathematics 2018-10-11 Anna Czapkiewicz , Antoni Dawidowicz

We present a new approach to the bootstrap for chains of infinite order taking values on a finite alphabet. It is based on a sequential Bootstrap Central Limit Theorem for the sequence of canonical Markov approximations of the chain of…

Probability · Mathematics 2007-05-23 P. Collet , D. Duarte , A. Galves

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

Peng (2006) initiated a new kind of central limit theorem under sub-linear expectations. Song (2017) gave an estimate of the rate of convergence of Peng's central limit theorem. Based on these results, we establish a new kind of almost sure…

Probability · Mathematics 2018-10-19 Weihuan Huang , Panyu Wu

In this paper, we establish an almost sure central limit theorem for a general random sequence under a strong approximation condition. Additionally, we derive the law of the iterated logarithm for the center of mass corresponding to a…

Probability · Mathematics 2024-07-08 Zhishui Hua , Wei Wanga , Liang Dong

In this paper, we study almost sure central limit theorems for multiple stochastic integrals and provide a criterion based on the kernel of these multiple integrals. We apply our result to normalized partial sums of Hermite polynomials of…

Probability · Mathematics 2009-04-15 Bernard Bercu , Ivan Nourdin , Murad S. Taqqu

In this paper, we study almost sure central limit theorems for sequences of functionals of general Gaussian fields. We apply our result to non-linear functions of stationary Gaussian sequences. We obtain almost sure central limit theorems…

Probability · Mathematics 2009-12-15 Bernard Bercu , Ivan Nourdin , Murad Taqqu

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

In this work we study and establish some quenched functional Central Limit Theorems (CLTs) for stationary random fields under a projective criteria. These results are functional generalizations of the theorems obtained by Zhang et al.…

Dynamical Systems · Mathematics 2024-05-28 Lucas Reding , Na Zhang

Adaptive and interacting Markov Chains Monte Carlo (MCMC) algorithms are a novel class of non-Markovian algorithms aimed at improving the simulation efficiency for complicated target distributions. In this paper, we study a general…

Statistics Theory · Mathematics 2011-07-15 Gersende Fort , Eric Moulines , Pierre Priouret , Pierre Vandekerkhove

Bifurcating Markov chains (BMC) are Markov chains indexed by a full binary tree representing the evolution of a trait along a population where each individual has two children. We provide a central limit theorem for additive functionals of…

Probability · Mathematics 2021-06-16 S. Valère Bitseki Penda , Jean-François Delmas

In this paper, we establish a version of the central limit theorem for Markov-Feller continuous time processes (with a Polish state space) that are exponentially ergodic in the bounded-Lipschitz distance and enjoy a continuous form of the…

Probability · Mathematics 2023-10-09 Dawid Czapla , Katarzyna Horbacz , Hanna Wojewódka-Ściążko

This paper develops central limit theorems (CLT's) and large deviations results for additive functionals associated with reflecting diffusions in which the functional may include a term associated with the cumulative amount of boundary…

Probability · Mathematics 2014-07-10 Peter W. Glynn , Rob J. Wang

Bifurcating Markov chains (BMC) are Markov chains indexed by a full binary tree representing the evolution of a trait along a population where each individual has two children. We provide a central limit theorem for general additive…

Probability · Mathematics 2022-07-02 S. Valère Bitseki Penda , Jean-François Delmas

We prove a central limit theorem for a general class of adaptive Markov Chain Monte Carlo algorithms driven by sub-geometrically ergodic Markov kernels. We discuss in detail the special case of stochastic approximation. We use the result to…

Probability · Mathematics 2009-11-03 Yves F. Atchade , Gersende Fort