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Let $(A_n)_{n\in\mathbb{N}}$ be a stationary sequence of topical (i.e., isotone and additively homogeneous) operators. Let $x(n,x_0)$ be defined by $x(0,x_0)=x_0$ and $x(n+1,x_0)=A_nx(n,x_0)$. It can model a wide range of systems including…

Probability · Mathematics 2007-10-30 Glenn Merlet

We establish central limit theorems for general functionals on binomial point processes and their Poissonized version. As an application, a central limit theorem for Betti numbers of random geometric complexes in the thermodynamic regime is…

Probability · Mathematics 2018-04-10 Khanh Duy Trinh

We present normal approximation results at the process level for local functionals defined on dynamic Poisson processes in $\mathbb{R}^d$. The dynamics we study here are those of a Markov birth-death process. We prove functional limit…

Probability · Mathematics 2022-10-25 Efe Onaran , Omer Bobrowski , Robert J. Adler

This paper provides a Central Limit Theorem (CLT) for a process $\{\theta_n, n\geq 0\}$ satisfying a stochastic approximation (SA) equation of the form $\theta_{n+1} = \theta_n + \gamma_{n+1} H(\theta_n,X_{n+1})$; a CLT for the associated…

Probability · Mathematics 2013-09-13 Gersende Fort

We obtain sufficient conditions for belonging of almost all paths of a random process to some fixed rearrangement invariant (r.i.) Banach functional space, and to satisfying the Central Limit Theorem (CLT) in this space. We describe also…

Probability · Mathematics 2014-09-09 E. Ostrovsky , L. Sirota

We consider the spectral properties of a class of regularized estimators of (large) empirical covariance matrices corresponding to stationary (but not necessarily Gaussian) sequences, obtained by banding. We prove a law of large numbers…

Probability · Mathematics 2009-01-22 Greg W. Anderson , Ofer Zeitouni

This is an expository review paper elaborating on the proof of the martingale functional central limit theorem (FCLT). This paper also reviews tightness and stochastic boundedness, highlighting one-dimensional criteria for tightness used in…

Probability · Mathematics 2007-12-27 Ward Whitt

We prove the Central Limit Theorem (CLT), the first order Edgeworth Expansion and a Mixing Local Central Limit Theorem (MLCLT) for Birkhoff sums of a class of unbounded heavily oscillating observables over a family of full-branch piecewise…

Dynamical Systems · Mathematics 2025-12-08 Kasun Fernando , Tanja I. Schindler

We formulate and prove a new sufficient conditions for Central Limit Theorem(CLT) in the space of continuous functions in the terms typical for the approximation theory. We prove that the conditions for continuous CLT obtained by N.C.Jain…

Probability · Mathematics 2013-04-02 E. Ostrovsky , L. Sirota

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 extend the spectral method for proving limit theorems to random non-uniformly expanding dynamical systems. This yields the CLT and moderate deviations principles (MDP). We show that as the amount of non-uniformity decreases the CLT rates…

Dynamical Systems · Mathematics 2024-08-14 Yeor Hafouta

In this paper, we build upon the asymptotic theory for GARCH processes, considering the general class of augmented GARCH($p$, $q$) processes. Our contribution is to complement the well-known univariate asymptotics by providing a joint…

Statistics Theory · Mathematics 2019-12-24 Marcel Bräutigam , Marie Kratz

By using limit theorems of uniform mixing Markov processes and martingale difference sequences, the strong law of large numbers, central limit theorem, and the law of iterated logarithm are established for additive functionals of…

Probability · Mathematics 2019-04-08 Jianhai Bao , Feng-Yu Wang , Chenggui Yuan

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

We prove a sequence of limiting results about weakly dependent stationary and regularly varying stochastic processes in discrete time. After deducing the limiting distribution for individual clusters of extremes, we present a new type of…

Probability · Mathematics 2017-12-05 Bojan Basrak , Hrvoje Planinic , Philippe Soulier

The central limit theorem for Markov chains generated by iterated function systems consisting of orientation preserving homeomorphisms of the interval is proved. We study also ergodicity of such systems.

Dynamical Systems · Mathematics 2020-03-24 Klaudiusz Czudek , Tomasz Szarek

A sharp version of the Central Limit Theorem for linear combinations of iterates of an inner function is proved. The authors previously showed this result assuming a suboptimal condition on the coefficients of the linear combination. Here…

Complex Variables · Mathematics 2024-07-25 Artur Nicolau , Odí Soler i Gibert

We present limit theorems for a sequence of Piecewise Deterministic Markov Processes (PDMPs) taking values in a separable Hilbert space. This class of processes provides a rigorous framework for stochastic spatial models in which discrete…

Probability · Mathematics 2012-04-13 Martin G. Riedler , Michèle Thieullen , Gilles Wainrib

We derive a necessary and sufficient condition for stochastic processes to have almost periodic finite dimensional distributions; in particular, we obtain characterizations for infinitely divisible processes to be almost periodic in terms…

Probability · Mathematics 2022-08-18 David Berger , Farid Mohamed

Stationary determinantal point processes are proved to be Brillinger mixing. This property is an important step towards asymptotic statistics for these processes. As an important example, a central limit theorem for a wide class of…

Statistics Theory · Mathematics 2015-07-24 Christophe Ange Napoléon Biscio , Frédéric Lavancier
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