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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

In this paper we consider the asymptotic distributions of functionals of the sample covariance matrix and the sample mean vector obtained under the assumption that the matrix of observations has a matrix-variate location mixture of normal…

Statistics Theory · Mathematics 2023-04-19 Taras Bodnar , Stepan Mazur , Nestor Parolya

In this article we review recent generalisations of the central limit theorem for the sum of specially correlated (or q-independent) variables, focusing on q greater or equal than 1. Specifically, this kind of correlation turns the…

Statistical Mechanics · Physics 2007-12-16 Silvio M. Duarte Queiros , Constantino Tsallis

In this talk I first review at an elementary level a selection of central limit theorems, including some lesser known cases, for sums and maxima of uncorrelated and correlated random variables. I recall why several of them appear in…

Statistical Mechanics · Physics 2010-08-26 H. J. Hilhorst

In this article, we prove that from any sequence of balls whose associated limsup set has full $\mu$-measure, one can extract a well-distributed subsequence of balls. From this, we deduce the optimality of various lower bounds for the…

Metric Geometry · Mathematics 2022-08-05 Édouard Daviaud

Let $f:[0,1)^d \to {\mathbb R}$ be an integrable function. An objective of many computer experiments is to estimate $\int_{[0,1)^d} f(x) dx$ by evaluating f at a finite number of points in [0,1)^d. There is a design issue in the choice of…

Statistics Theory · Mathematics 2007-08-07 Wei-Liem Loh

Motivated by the central limit problem for convex bodies, we study normal approximation of linear functionals of high-dimensional random vectors with various types of symmetries. In particular, we obtain results for distributions which are…

Probability · Mathematics 2016-09-07 Elizabeth S. Meckes , Mark W. Meckes

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

Motivated by problems on random differences in Szemer\'{e}di's theorem and on large deviations for arithmetic progressions in random sets, we prove upper bounds on the Gaussian width of point sets that are formed by the image of the…

Combinatorics · Mathematics 2018-10-22 Jop Briët , Sivakanth Gopi

We provide a Lyapunov type bound in the multivariate central limit theorem for sums of independent, but not necessarily identically distributed random vectors. The error in the normal approximation is estimated for certain classes of sets,…

Probability · Mathematics 2019-07-24 Martin Raič

We prove a randomized version of the generalized Urysohn inequality relating mean-width to the other intrinsic volumes. To do this, we introduce a stochastic approximation procedure that sees each convex body K as the limit of intersections…

Metric Geometry · Mathematics 2016-06-30 Grigoris Paouris , Peter Pivovarov

Suppose $B_i:= B(p,r_i)$ are nested balls of radius $r_i$ about a point $p$ in a dynamical system $(T,X,\mu)$. The question of whether $T^i x\in B_i$ infinitely often (i. o.) for $\mu$ a.e.\ $x$ is often called the shrinking target problem.…

Dynamical Systems · Mathematics 2015-06-16 Nicolai Haydn , Matthew Nicol , Sandro Vaienti , Licheng Zhang

We consider the random walk among random conductances on Z^d. We assume that the conductances are independent, identically distributed and uniformly bounded away from 0 and infinity. We obtain a quantitative version of the central limit…

Probability · Mathematics 2011-05-24 Jean-Christophe Mourrat

We prove a pointwise version of the multi-dimensional central limit theorem for convex bodies. Namely, let X be an isotropic random vector in R^n with a log-concave density. For a typical subspace E in R^n of dimension n^c, consider the…

Metric Geometry · Mathematics 2007-08-21 Ronen Eldan , Bo'az Klartag

We extend the recent spectral approach for quenched limit theorems developed for piecewise expanding dynamics under general random driving [DrFrGTVa18] to quenched random piecewise hyperbolic dynamics including some classes of billiards.…

Dynamical Systems · Mathematics 2018-12-19 D. Dragičević , G. Froyland , C. González-Tokman , S. Vaienti

For every vector $\overline \alpha\in \RR^n$ and for every rational approximation $(\overline p,q)\in \RR^n\times\RR$ we can associate the displacement vector $q\alpha-\overline p$. We focus on algebraic vectors, namely $\overline…

Dynamical Systems · Mathematics 2025-05-29 Yuval Yifrach

We provide a simple proof for of the central limit theorem for the number of vertices in the giant for super-critical stochastic block model using the breadth-first walk of Konarovskyi, Limic and the author (2024). Our approach follows the…

Probability · Mathematics 2025-01-03 David Clancy

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 Berry-Esseen theorem, a local central limit theorem and (local) large and (global) moderate deviations principles for i.i.d. (uniformly) random non-uniformly expanding or hyperbolic maps with exponential first return times. Using…

Dynamical Systems · Mathematics 2021-07-19 Yeor Hafouta

First, we prove a \emph{local almost sure central limit theorem} for lattice random walks in the plane. The corresponding version for random walks in the line was considered by the author in \cite{5}. This gives us a quantitative version of…

Probability · Mathematics 2014-05-13 Nuno Luzia
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