ψ-混合序列加权和的完全收敛性

研究Ψ-混合序列加权和的完全收敛性,证明了一般双下标加权系数的加权部分和的完全收敛性,改进了杨善朝的结果.     

两两NQD阵列加权和的完全收敛性

本文研究行两两NQD阵列加权和的完全收敛性,证明了一般双下标加权系数的加权部分和的完全收敛性,推广了文献[8]的结果.     

ρ^ ～混合序列加权和完全收敛性和强收敛性

讨论了ρ^ ～混合序列加权和完全收敛性和强收敛性，推广了Stout和Thrum定理。     

NOD随机变量序列加权和的矩完全收敛性

讨论了NOD随机变量序列加权和的矩完全收敛性,获得了NOD随机变量序列加权和的矩完全收敛性的充要条件.这些结论显示了矩完全收敛性和矩条件之间的等价关系,同时推广了Wu Qunying(2011)的结果.     

ρ-混合序列加权和的完全收敛性

本文讨论了不同分布ρ-混合序列部分和的完全收敛性,建立了一个定理.然后通过此非加权和的完全收敛性定理来研究加权和的完全收敛性定理,从而改进了前人所获得的已有的一些结果.     

两两NQD阵列加权和的收敛性质

研究了不同分布行两两NQD阵列加权和的Lp收敛性和完全收敛性，改进了前人的结果．     

行为负相依随机变量阵列加权和的完全收敛性

本文研究了行为NOD随机变量阵列加权和的完全收敛性.运用NOD随机变量列的矩不等式以及截尾的方法,得到了关于行为NOD随机变量阵列加权和的完全收敛性的充分条件.利用获得的充分条件,推广了Baek(2008)关于行为NA随机变量阵列加权和的完全收敛性的结论,得到了比吴群英(2012)更为一般的结果.     

次线性期望空间下END阵列加权和的完全收敛性

在Choquet积分存在的条件下,研究次线性期望空间下END阵列加权和的完全收敛性,将概率空间中END阵列加权和的完全收敛性推广到次线性期望空间.     

NA列加权乘积和的完全收敛性

本文讨论了NA和几类加权部分和及加权乘积和的完全收敛性，其中部分结果要优于iid列的已知结论。     

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。     

Moment Complete Convergence for Weighted Sums of -Mixing Random Variables

In this paper, the authors discuss the moment complete convergence for weighted sums of -mixing random variables, and obtains the sufficient condition for moment complete convergence of -mixing sequence under some mixing rate condition, which generalize the result of moment complete convergence for weighted sums of i.i.d. random variables to -mixing random variables.     

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??In this paper, the complete moment convergence for weighted sums of-mixing random variable series are investigated. By using Rosenthal type inequality, we obtain complete moment convergence theorems for weighted sums of-mixing random variable series, which generalize and improve the corresponding results.     

Complete Convergence of Weighted Sums for Arrays of Rowwise m-negatively Asso ciated Random Variables

In this paper, we discuss the complete convergence of weighted sums for arrays of rowwise m-negatively associated random variables. By applying moment inequality and truncation methods, the sufficient conditions of complete convergence of weighted sums for arrays of rowwise m-negatively associated random variables are established. These results generalize and complement some known conclusions.     

Complete Convergence of Weighted Sums for Arrays of Rowwise $m$-Negatively Associated Random Variables

In this paper, we discuss the complete convergence of weighted sums for arrays of rowwise $m$-negatively associated random variables. By applying moment inequality and truncation methods, the sufficient conditions of complete convergence of weighted sums for arrays of rowwise $m$-negatively associated random variables are established. These results generalize and complement some known conclusions.     

行为混合阵列加权和的收敛性

本文研究了行为混合阵列加权和的收敛性.利用混合序列的Rosenthal型最大值不等式,讨论了混合阵列加权和的L1收敛性,依概率收敛性,几乎处处收敛性,及完全收敛性之间的等价关系,推广了行独立随机变量阵列相应的结果.     

Complete and complete moment convergence for weighted sums of widely orthant dependent random variables

In this paper, we establish a complete convergence result and a complete moment convergence result for weighted sums of widely orthant dependent random variables under mild conditions. As corollaries, the corresponding results for weighted sums of extended negatively orthant dependent random variables are also obtained, which generalize and improve the related known works in the literature.     

Complete Convergence and Complete Moment Convergence for Maximal Weighted Sums of Extended Negatively Dependent Random Variables

In this paper,the complete convergence and complete moment convergence for maximal weighted sums of extended negatively dependent random variables are investigated.Some sufficient conditions for the convergence are provided.In addition,the Marcinkiewicz–Zygmund type strong law of large numbers for weighted sums of extended negatively dependent random variables is obtained.The results obtained in the article extend the corresponding ones for independent random variables and some dependent random variables.     

Complete Convergence for Weighted Sums of WOD Random Variables

In this article, we study the complete convergence for weighted sums of widely orthant dependent random variables. By using the exponential probability inequality, we establish a complete convergence result for weighted sums of widely orthant dependent ran-dom variables under mild conditions of weights and moments. The result obtained in the paper generalizes the corresponding ones for independent random variables and negatively dependent random variables.     

关于随机变量加权和的强收敛性注记

设{X,;n≥1}为独立同分布随机序列,{a_(xi);1≤i≤K_n,↑~∞,n≥1}为权系数序列。本文给出三组sum from i=1 to K_n(a_(ai)X_i→0a.s.充分条件。同时,还讨论加权和的完全收敛性,我们的条件比[3]弱。