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We obtain asymptotic expansions for probabilities $\mathbb{P}(S_N=k)$ of partial sums of uniformly bounded integer-valued functionals $S_N=\sum_{n=1}^N f_n(X_n)$ of uniformly elliptic inhomogeneous Markov chains. The expansions involve…

Probability · Mathematics 2022-03-31 Dmitry Dolgopyat , Yeor Hafouta

We study Edgeworth expansions in limit theorems for self-normalized sums. Non-uniform bounds for expansions in the central limit theorem are established while only imposing minimal moment conditions. Within this result, we address the case…

Probability · Mathematics 2022-08-11 Pascal Beckedorf , Angelika Rohde

This paper provides a finite sample bound for the error term in the Edgeworth expansion for a sum of independent, potentially discrete, nonlattice random vectors, using a uniform-in-$P$ version of the weaker Cram\'{e}r condition in Angst…

Statistics Theory · Mathematics 2019-08-14 Kyungchul Song

We study the distribution of a general class of asymptoticallylinear statistics which are symmetric functions of $N$ independent observations. The distribution functions of these statistics are approximated by an Edgeworth expansion with a…

Statistics Theory · Mathematics 2021-02-09 Friedrich Götze , Mindaugas Bloznelis

In this article, we obtain explicit bounds on the uniform distance between the cumulative distribution function of a standardized sum $S_n$ of $n$ independent centered random variables with moments of order four and its first-order…

Probability · Mathematics 2025-07-30 Alexis Derumigny , Lucas Girard , Yannick Guyonvarch

We prove Edgeworth type expansions for distribution functions of sums of free random variables under minimal moment conditions. The proofs are based on the analytic definition of free convolution. We apply these results to the expansion of…

Probability · Mathematics 2011-12-22 G. P. Chistyakov , F. Götze

We consider sums of independent identically distributed random variables whose distributions have $d+1$ atoms. Such distributions never admit an Edgeworth expansion of order $d$ but we show that for almost all parameters the Edgeworth…

Probability · Mathematics 2023-06-21 Dmitry Dolgopyat , Kasun Fernando

Edgeworth-type expansions for convolutions of probability densities and powers of the characteristic functions with non-uniform error terms are established for i.i.d. random variables with finite (fractional) moments of order $s \geq 2$,…

Probability · Mathematics 2011-04-20 S. G. Bobkov , G. P. Chistyakov , F. Götze

An Edgeworth-type expansion is established for the entropy distance to the class of normal distributions of sums of i.i.d. random variables or vectors, satisfying minimal moment conditions.

Probability · Mathematics 2013-07-25 Sergey G. Bobkov , Gennadiy P. Chistyakov , Friedrich Götze

We study asymptotic expansions in free probability. In a class of classical limit theorems Edgeworth expansion can be obtained via a general approach using sequences of "influence" functions of individual random elements described by…

Probability · Mathematics 2015-02-05 F. Götze , A. Reshetenko

We establish higher-order nonasymptotic expansions for a difference between probability distributions of sums of i.i.d. random vectors in a Euclidean space. The derived bounds are uniform over two classes of sets: the set of all Euclidean…

Statistics Theory · Mathematics 2022-11-30 Mayya Zhilova

We explore some properties of the conditional distribution of an i.i.d. sample under large exceedances of its sum. Thresholds for the asymptotic independance of the summands are observed, in contrast with the classical case when the…

Statistics Theory · Mathematics 2016-10-14 Maeva Biret , Michel Broniatowski , Zangsheng Cao

A sum of observations derived by a simple random sampling design from a population of independent random variables is studied. A procedure finding a general term of Edgeworth asymptotic expansion is presented. The Lindeberg condition of…

Statistics Theory · Mathematics 2013-12-12 Ibrahim Bin Mohamed , Sherzod M. Mirakhmedov

Consider the matrix products $G_n: = g_n \ldots g_1$, where $(g_{n})_{n\geq 1}$ is a sequence of independent and identically distributed positive random $d\times d$ matrices. Under the optimal third moment condition, we first establish a…

Probability · Mathematics 2025-02-20 Hui Xiao , Ion Grama , Quansheng Liu

A large class of statistics can be formulated as smooth functions of sample means of random vectors. In this paper, we propose a general partial Cram\'{e}r's condition (GPCC) and apply it to establish the validity of the Edgeworth expansion…

Probability · Mathematics 2025-11-04 Yashi Wei , Jiang Hu , Zhidong Bai

We prove an asymptotic Edgeworth expansion for the profiles of certain random trees including binary search trees, random recursive trees and plane-oriented random trees, as the size of the tree goes to infinity. All these models can be…

Probability · Mathematics 2017-10-06 Zakhar Kabluchko , Alexander Marynych , Henning Sulzbach

Classical Edgeworth expansions provide asymptotic correction terms to the Central Limit Theorem (CLT) up to an order that depends on the number of moments available. In this paper, we provide subsequent correction terms beyond those given…

Probability · Mathematics 2011-03-23 Henry Lam , Jose Blanchet , Damian Burch , Martin Z. Bazant

We obtain non-uniform Edgeworth expansions for several classes of weakly dependent (non-stationary) sequences of random variables, including uniformly elliptic inhomogeneous Markov chains, random and time-varying (partially) hyperbolic or…

Probability · Mathematics 2025-11-11 Yeor Hafouta

The "typical" asymptotic behavior of the weighted sums of independent, identically distibuted random vectors in k-dimensional space is considered. It is shown that under finitnes of fifth absolute moment of an individual term the rate of…

Probability · Mathematics 2023-12-25 Sagak Ayvazyan

Edgeworth expansions for random walks on covering graphs with groups of polynomial volume growths are obtained under a few natural assumptions. The coefficients appearing in this expansion depends on not only geometric features of the…

Probability · Mathematics 2023-06-05 Ryuya Namba
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