A Berry-Esséen bound for student's statistic in the non-I.I.D. case

We establish a Berry-Esséen bound for Student's statistic for independent (nonidentically) distributed random variables. In particular, the bound implies a sharp estimate similar to the classical Berry-Esséen bound. In the i.i.d. case it yields sufficient conditions for the Central Limit Theorem for studentized sums. For non-i.i.d. random variables the bound shows that the Lindeberg condition is sufficient for the Central Limit Theorem for studentized sums.Research supported by the SFB 343 in Bielefeld.     

负相协重尾随机变量和的尾概率的渐近性的若干注记

本文得到了同分布负相协重尾随机变量和的最大值、随机个和的最大值尾概率的渐进性质\bd所得到的结果削弱了Wang和Tang (Statist. Prob. Lett., 68, 287--295, 2004)$^{[1]}$的Theorem 2.1的矩条件, 在与[1]的Theorem 2.2不同的条件下得到了相应的结果, 并且都解除了上述[1]的结果中对随机变量的支撑的限制.     

Supply of harmonic functions of an infinite number of variables. III

We obtain optimal (in a certain sense) harmonicity conditions on functions on a Hilbert space which follow from estimates for sums of independent random variables. Together with the harmonicity conditions obtained earlier, based on estimates of the order of growth for sums of dependent random variables and for sums of orthogonal random variables, they make it possible to consider new classes of harmonic functions of an infinite number of variables.Translated from Ukrainskii Matematicheskii Zhurnal, Vol. 44, No. 3, pp. 417–423, March, 1992.     

随机变数配重和的两个收敛定理

本文给出随机变数配重和几乎必然收敛的两个定理,同时讨论了可分赋范线性空间中随机元的相应推广。 定理1 设随机变数序列{x_n}的律一致地以一个随机变数X的律为界,即对所有n和     

不同分布NA序列加权和的完全收敛性

本文讨论了不同分布NA随机变量序列加权和的完全收敛性，获得了较[7]中的定理1及定理A更为一般的安全收敛性，并得到了完全收敛速度与矩条件之间的等价关系。     

Supply of harmonic functions of an infinite number of variables. II

There are exceptionally many harmonic functions of an infinite number of variables. Using for the estimate of the infinite-dimensional Laplacian introduced by P. Levy, estimates of the germ of sums of orthogonal random variables, there are obtained optimal (in a certain sense) conditions of the harmonicity of the functions in a Hilbert space. Along with harmonicity conditions obtained earlier based on estimates of the germ of sums of dependent random variables, they allow one to encompass the manifold of harmonic functions of an infinite number of variables.Translated from Ukrainskii Matematicheskii Zhurnal, Vol. 42, No. 12, pp. 1687–1693, December, 1990.     

A general estimate in the invariance principle

We obtain estimates for the accuracy with which a random broken line constructed from sums of independent nonidentically distributed random variables can be approximated by a Wiener process. All estimates depend explicitly on the moments of the random variables; meanwhile, these moments can be of a rather general form. In the case of identically distributed random variables we succeed for the first time in constructing an estimate depending explicitly on the common distribution of the summands and directly implying all results of the famous articles by Komlós, Major, and Tusnády which are devoted to estimates in the invariance principle.     

Exponential tail estimates in the law of ordinary logarithm (LOL) for triangular arrays of random variables

We derive exponential bounds for the tail of the distribution of normalized sums of triangular arrays of random variables, not necessarily independent, under the law of ordinary logarithm.

Furthermore, we provide estimates for partial sums of triangular arrays of independent random variables belonging to suitable grand Lebesgue spaces and having heavy-tailed distributions.

     

Independent Random Variables in Lorentz Spaces

We investigate random variables in Lorentz spaces L_p,q. Conditionson the characteristic function are obtained which imply thata random variable belongs to the Lorentz space. Using them,we prove some estimates for the L_p,q-norm of sums of independentrandom variables. Some of these estimates are new for the spacesL_p.     

THE ERDOS-RENYI LAWS OF LARGE NUMBERS FOR NON-IDENTICALLY DISTRIBUTED RANDOM VARIABLES

The Erdos-Renyi law of large numbers (1970) is the first important result forasymptotic behaviours of increments of partial sams of a sequence of random variableswith apan [ClogN]. Some generalizations have been done sinoe then, such as conver-gence rate of the limit, some results when order of span being either higher or lowerthan log N. But all these results are only obtained in the case of i. i. d. random variables.This paper aims at the generalization of these results to the ease when random variablesare independent, but not necessarily identically distributed. To this end Chernoff Theoremis generalized to the corlesponding case at first.     

The convergence of moments in the martingale central limit theorem

Summary An early extension of the Lindeberg-Feller Theorem was Bernstein's discovery of necessary and sufficient conditions for the convergence of moments in the central limit theorem for sums of independent random variables. In this paper we show that Bernstein's work has a generalisation to martingales. We extend his work in both the independence and the martingale cases by showing that there exists a duality between the behaviour of the moments of the martingale and the behaviour of the sums of squares of the martingale differences. Our proofs are quite unrelated to Bernstein's and are based on Burkholder's inequalities.     

The strong law of large numbers for a stationary sequence

General results on the applicability of the strong law of large numbers to a sequence of dependent random variables, as formulated in terms of estimates for the moments of sums of such variables, are applied to give new conditions of the applicability of this law to (in a wide sense) a stationary sequence of random variables.     

The Intersective ASCLT

Abstract

In a recent work of the second named author on the Almost Sure Central Limit Theorem (ASCLT), we showed the usefulness of the concept of quasi-orthogonal system of random variables introduced by Bellman and later developed by Kac, Salem and Zygmund. In this paper, we propose an optimal formulation of the ASCLT again by using this idea and new correlation inequalities for sums of independent random variables. We also introduce and develop the notion of “intersective ASCLT” by proving some new results generalizing and improving substancially the classical formulation of the ASCLT. Essential tools for this approach are correlation inequalities recently developed by the first named author and some extensions of these ones obtained in the present paper.     

On the Growth of Sums of Nonnegative Random Variables

Almost sure estimates of the growth of sums of nonnegative random variables are established. A generalization of author's result on the growth of sums of the indicators of arbitrary events is obtained. Bibliography: 10 titles. __________ Translated from Zapiski Nauchnykh Seminarov POMI, Vol. 311, 2004, pp. 237–241.     

I.I.D.随机变量两两乘积之和的Hsu-Robbins型定理(II)

在本部分中,采用由Levy函数(4.1)所确定的值b     

Estimates in the invariance principle in terms of truncated power moments

We obtain estimates for the distributions of errors which arise in approximation of a random polygonal line by a Wiener process on the same probability space. The polygonal line is constructed on the whole axis for sums of independent nonidentically distributed random variables and the distance between it and the Wiener process is taken to be the uniform distance with an increasing weight. All estimates depend explicitly on truncated power moments of the random variables which is an advantage over the earlier estimates of Komlos, Major, and Tusnady where this dependence was implicit.     

I.I.D.随机变量两两乘积之和的Hsu-Robbins型定理(Ⅱ)

在本部分中,采用由 Ｌｅｖｙ函数（４．ｌ）所确定的值ｂｎ取代（Ｉ）［１］中的１／ｎ“位点”ａｎ,使得（Ｉ）中定理１中的附加条件（Ａ）得以解除,从而获得了可以称之为Ｈｓｕ－Ｒｏｂｂｉｎｓ型的充分必要条件．作为推论,还给出了两个互为复制的ｉｉｄ随机变量三角阵对应行之和乘积的Ｋｏｌｍｏｇｏｒｏｖ强大数律．     

An extension of Vietoris's inequalities

We establish a best possible extension of a famous Theorem of Vietoris about the positivity of a general class of cosine sums. Our result refines and sharpens several earlier generalizations of this Theorem, and settles some open questions regarding the possibility of further improvement of it. Some new inequalities for trigonometric sums are given. We show that our results have applications within the context of positive sums of Gegenbauer polynomials and quadrature methods. We also obtain some existing estimates for the location of zeros of certain trigonometric polynomials under a weakened condition on their coefficients. 2000 Mathematics Subject ClassificationPrimary—42A05; Secondary—42A32,26D05, 26D15, 33B15, 33C45 Dedicated to Richard Askey on the occasion of his 70th birthday     

关于N-弱鞅和弱鞅不等式的一个注记

$N$-弱鞅($N$-demimartingales)是由Christofides引进的.Christofides指出均值为零的负相协(negatively associated)随机变量序列的部分和序列是$N$-弱鞅. 然而, 相关文献中引理2.1的证明有错误, 这就影响了其文后的结果引理2.2、定理2.1等. 在这篇注记中,修正了相关文献中的引理2.1, 作为应用, 推广了鞅和下鞅的一些结果.     

A Central Limit Theorem for linear random fields

A Central Limit Theorem is proved for linear random fields when sums are taken over union of finitely many disjoint rectangles. The approach does not rely upon the use of Beveridge-Nelson decomposition and the conditions needed are similar in nature to those given by Ibragimov for linear processes. When specializing this result to the case when sums are being taken over rectangles, a complete analogue of the Ibragimov result is obtained for random fields with a lot of uniformity.