H-值半鞅测度的弱收敛

本文引进了H-值半鞅测度，研究了其基本性质和与之相联系的随机积分，本文还引入了H-值半鞅测度序列依分布弱收敛的概念，建立了H-值半鞅测度的极限定理，给出了H-值半鞅测度弱收敛的条件。     

集值条件期望的收敛定理

本文给出了集合序列弱极限的表示定理，得到了随机集列关于σ－域流的条件期望序列在弱收敛意义的Fatou型引理和控制收敛定理。     

关于关联随机变量序列的极限收敛定理

本文给出了两两PQD的随机变量序列的级数收敛及加权部分和的稳定性的两个结果。另给出了相伴(associated)序列加权和的稳定性的一个结果。最后给出了一个级数收敛定理条件不能减弱的反例。     

随机过程序列部分和的收敛性

本文讨论了随机过程序列部分和的收敛性问题，给出了部分和过程弱收敛于Gauss过程的条件，得到了随机过程序列场合的嵌入定理及强逼近定理．     

Orlicz序列空间的弱收敛序列系数

本文给出了Orlicz序列空间的弱收敛序列系数的表达式.     

一类可数离散半群上概率测度序列的组合收敛性

本文讨论具有单位元的可数离散半群上概率测度序列的组合收敛性，主要结果推广了有限群上的Ｍａｋｓｉｍｏｖ定理，同时也蕴含了Ｃｅｎｔｅｒ，Ｍｕｋｈｅｒｊｅａ等人的一些结论．     

NA序列中心极限定理的收敛速度

本文对NA（NegativelyAssociated）序列建立了中心极限定理的一致收敛速度，只要其三阶矩有限及描述NA序列协方差结构的一个系数u（n）被负指数序列所控制，而无需平稳性便获得了其收敛速度O（n(-1/2)logn）。     

m-LNQD序列部分和的若干极限定理

作者提出了m-LNQD (m-linearly negative quadrant dependent)相依结构概念.首先给出了m-LNQD序列部分和的一个概率不等式,进而获得了m-LNQD序列的若干极限定理,推广了已有的结果.     

局部紧群上概率测度卷积幂弱收敛等价性定理

本文研究拓扑代数结构上概率测度的极限性质。把Kawada-Ito等人在紧群上得到的有关卷积幂弱收敛等价性的经典结果完整地推广到局部紧群上。     

概率算子测度弱收敛的一个方法

本文给出一个新的概率算子测度弱收敛的充要条件。     

关于任意相依随机序列的完全收敛性(英文)

引入极限对数似然比的概念作为任意随机序列的联合分布与其边缘分布的差异的随机性度量,用概率密度比构造几乎处处收敛的上鞅,在适当的条件下,给出任意随机序列完全收敛的若干定理.     

关于任意非负随机序列随机和的一类随机偏差定理

本文引入任意随机变量序列随机极限对数似然比概念,作为任意相依随机序列联合分布与其边缘乘积分布“不相似”性的一种度量,利用构造新的密度函数方法来建立几乎处处收敛的上鞅,在适当的条件下,给出了任意受控随机序列的一类随机偏差定理.     

NA序列完全矩收敛精确渐近性的一般结果

本文利用NA序列的弱收敛定理及概率不等式,证明了其完全矩收敛精确渐近性的一般结果,改进并推广了已有的结果.     

离散随机序列随机和的一类强偏差定理

In this paper, the notion of limit random logarithmic likelihood ratio of stochastic se-quences,as a measure of “dissimilarity“ between their joint distributions and the product of theirmarginals,is introduced. Construct a. s. convergence supermartingale by means of truncation methodand under suitable restrict Chung-Teicher type conditions,some strong deviation theorems for arbi-trary discrete stochastic sequence are obtained.     

Statistical Convergence in Probability for a Sequence of Random Functions

In this paper, we introduce a new type of convergence for a sequence of random functions, namely, statistical convergence in probability, which is a natural generalization of convergence in probability. In this approach, we allow such a sequence to go far away from the limit point infinitely many times by presenting random deviations, provided that these deviations are negligible in some sense of measure. In this context, the set of values of a random function is considered as a probabilistic metric (PM) space of random variables, and some basic results are obtained using the tools of PM spaces.     

Weak Convergence of a Sequence of Semimartingales to a Diffusion with Discontinuous Drift and Diffusion Coefficients

This paper presents a set of sufficient conditions for a sequence of semimartingales to converge weakly to a solution of a stochastic differential equation (SDE) with discontinuous drift and diffusion coefficients. This result is closely related to a well-known weak-convergence theorem due to Liptser and Shiryayev (see [27]) which proves the weak convergence to a solution of a SDE with continuous drift and diffusion coefficients in the Skorokhod–Lindvall J ₁-topology.The goal of this paper is to obtain a stronger result in order to solve outstanding problems in the area of large-scale queueing networks – in which the weak convergence of normalized queueing length is a solution of a SDE with discontinuous coefficients. To do this we need to make the stronger assumptions: (1) replacing the convergence in probability of the triplets of a sequence of semimartingales in the original Liptser and Shiryayev's theorem by stronger convergence in L ₂, (2) assuming the diffusion coefficient is coercive, and (3) assuming the discontinuity sets of the coefficients of the limit diffusion processs are of Lebesgue measure zero.     

局部紧H半群上概率测度卷积幂的弱收敛性

本文讨论局部紧Ｈ半概率测度卷积幂的弱收敛性,将紧群上的Ｋａｗａｄａ－Ｉｔｏ型结果以某种相应的形式建立到局部紧Ｈ半群,由于紧半群上的概率测度卷积幂序列必为 ,所以,不仅Ｋａｗａｄａ－Ｉｔｏ经典结果是本文的特例,而且「１」中的定理和「２」中的定理２都可以作为本文定理的推论     

任意随机序列级数的强收敛性

利用鞅差序列级数收敛定理研究任意随机序列级数的强收敛性,得到了该序列的一个强极限定理,某些经典的鞅差序列和独立随机变量序列的强极限定理是其特例.     

随机序列的变换及其局部强收敛性

本文引入任意随机变量序列停时变换的概念，利用截尾方法构造几乎处处收敛的鞅结合无穷乘积定理，讨论了变换的局部收敛性及强大数定理，作为推论得到了关于赌博系统的若干强极限定理。     

On conditional weak convergence

In this paper we discuss a number of technical issues associated with conditional weak convergence. The main modes of convergence of conditional probability distributions areuniform, probability, andalmost sure convergence in the conditioning variable. General results regarding conditional convergence are obtained, including details of sufficient conditions for each mode of convergence, and characterization theorems for uniform conditional convergence.