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This article studies the weak convergence and associated Central Limit Theorem for blurring and nonblurring processes. Then, they are applied to the estimation of location parameter. Simulation studies show that the location estimation…

Statistics Theory · Mathematics 2015-01-28 Ting-Li Chen , Hironori Fujisawa , Su-Yun Huang , Chii-Ruey Hwang

We prove uniform convergence results for the integrated periodogram of a weakly dependent time series, namely a law of large numbers and a central limit theorem. These results are applied to Whittle's parametric estimation. Under general…

Statistics Theory · Mathematics 2008-04-15 Jean-Marc Bardet , Paul Doukhan , José Rafael León

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 obtain central limit theorems for stationary random fields employing a novel measure of dependence called $\theta$-lex weak dependence. We show that this dependence notion is more general than strong mixing, i.e., it applies to a broader…

Statistics Theory · Mathematics 2021-04-07 Imma Valentina Curato , Robert Stelzer , Bennet Ströh

We prove a central limit theorem for linear triangular arrays under weak dependence conditions. Our result is then applied to the study of dependent random variables sampled by a $\bbZ$-valued transient random walk. This extends the results…

Probability · Mathematics 2007-12-24 Nadine Guillotin-Plantard , Clémentine Prieur

A central limit theorem is proved for some strictly stationary sequences of random variables that satisfy certain mixing conditions and are subjected to the "shrinking operators" $U_r(x):=[\max\{|x|-r,0\}]\cdot x/|x|,\ r \ge 0$. For…

Probability · Mathematics 2014-10-02 Richard C. Bradley , Zbigniew J. Jurek

We prove the Central Limit Theorem (CLT) from the definition of weak convergence using the Haar wavelet basis, calculus, and elementary probability. The use of the Haar basis pinpoints the role of $L^{2}([0,1])$ in the CLT as well as the…

Probability · Mathematics 2015-10-29 Vladimir Dobric , Patricia Garmirian

We deduce sufficient conditions for the Central Limit Theorem (CLT) in the Lebesgue-Riesz space L(p) defined on some measure space for the sequence of centered random variables satisfying the strong mixing (Rosenblatt) condition. We…

Probability · Mathematics 2019-12-05 M. R. Formica , E. Ostrovsky , L. Sirota

We study the Coulomb chain where particles are restricted to one dimension and experience three-dimensional Coulomb interactions with their nearest and next-to-nearest neighbours. The distances between consecutive particles are treated as…

Probability · Mathematics 2024-04-24 Henrik Ekström

We obtain the law of large numbers (LLN) and the central limit theorem (CLT) for weakly dependent non-stationary arrays of random fields with asymptotically unbounded moments. The weak dependence condition for arrays of random fields is…

Statistics Theory · Mathematics 2024-08-15 Yue Pan , Jiazhu Pan

General Central limit theorem deals with weak limits (in type) of sums of row-elements of array random variables. In some situations as in the invariance principle problem, the sums may include only parts of the row-elements. For strictly…

We prove a central limit theorem for a sequence of random variables whose means are ambiguous and vary in an unstructured way. Their joint distribution is described by a set of measures. The limit is (not the normal distribution and is)…

Probability · Mathematics 2020-07-01 Zengjing Chen , Larry G. Epstein

This paper provides central limit theorems for the wavelet packet decomposition of stationary band-limited random processes. The asymptotic analysis is performed for the sequences of the wavelet packet coefficients returned at the nodes of…

Information Theory · Computer Science 2009-10-26 Abdourrahmane Atto , Dominique Pastor

The standard central limit theorem with a Gaussian attractor for the sum of independent random variables may lose its validity in presence of strong correlations between the added random contributions. Here, we study this problem for…

Statistical Mechanics · Physics 2016-06-14 Adrian A. Budini

Central limit theorems are established for the sum, over a spatial region, of observations from a linear process on a $d$-dimensional lattice. This region need not be rectangular, but can be irregularly-shaped. Separate results are…

Statistics Theory · Mathematics 2016-01-07 S. N. Lahiri , Peter M. Robinson

The paper deals with a random connection model, a random graph whose vertices are given by a homogeneous Poisson point process on $\mathbb{R}^d$, and edges are independently drawn with probability depending on the locations of the two end…

Probability · Mathematics 2021-02-18 Van Hao Can , Khanh Duy Trinh

Linear processes are defined as a discrete-time convolution between a kernel and an infinite sequence of i.i.d. random variables. We modify this convolution by introducing decimation, that is, by stretching time accordingly. We then…

Statistics Theory · Mathematics 2008-12-18 François Roueff , Murad S. Taqqu

The main result of this paper is a general central limit theorem for distributions defined by certain renewal type equations. We apply this to weakly self-avoiding random walks. We give good error estimates and Gaussian tail estimates which…

Probability · Mathematics 2007-05-23 Erwin Bolthausen , Christine Ritzmann

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 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
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