随机度量空间及其应用

首先证明取值于度量空间(可分或不可分)的随机元可构成随机度量空间;取值于赋范空间的随机元可嵌入到随机赋范空间中.接着给出这些结论对随机算子的应用.最后统一给出赋范空间上几乎处处有界的随机线性泛函的表示.     

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     

在Hilbert空间与可分Banach空间关于随机级数的收缩原理

在Ｈｉｌｂｅｒｔ空间与可分Ｂａｎａｃｈ空间，用独立随机元收敛准则或三级数定理的思想，证明了关于随机级数的民上缩原理。     

关于序列覆盖s映射的注记

本文分别给出局部可分度量空间的强序列覆盖（1序列覆盖,2序列覆盖）。映象的新刻画,还分别给出拓扑空间是局部可分度量空间的序列覆盖（紧覆盖）s映象的一个充分条件．     

局部可分度量空间的序列覆盖s象

本文给出了局部可分度量空间的1序列覆盖s象,2序列覆盖s象,强序列覆盖s象,序列覆盖s象及子序列覆盖s象的内在刻划．从而使关于对度量空间的各类s象的内在刻划方面的研究更趋于完整．     

独立B-值随机元的中偏差

本文讨论了取值可分Banach空间的i. i. d.随机元序列的中偏差下限估计及开凸集上的中偏差极限问题,改进和推广了Borovkov-Mogul's kii及Deo-Babu的工作。     

局部可分度量空间的伪序列覆盖映射

指出了文[1]中的一个问题,并给出了局部可分度量空间的伪序列覆盖s映象和局部可分度量空间的伪序列覆盖紧映象的刻划。     

随机样本长度经验过程的极限定理

本文得到以函数为指标的随机样本长度经验过程的泛函中心极限定理．给出一列随机元关于某概率分布混合的充分条件．把Billingsley~［2，定理4．5］的一定理推广到非可分距离空间，并举了两个例子说明这些结果的应用．     

关于Banach空间最小系的扩充

本文就可分Banach空间中元素的最小序列(也称双直交序列)可以扩充到在全空间中完备这一事实,说明在空间不可分情况下,对于由不可数个元素组成的所谓最小系,这种完备性扩充未必可行.此外,还应用最小序列扩充性质给出可分的遗传不可分解空间的一个特征刻画.     

局部可分度量空间的序列覆盖局部可数象

本文给出了局部可分度量空间的序列复盖局部可数象的刻画。     

The almost sure local central limit theorem for the product of partial sums

We derive under some regular conditions an almost sure local central limit theorem for the product of partial sums of a sequence of independent identically distributed positive random variables.     

Central limit theorem and almost sure central limit theorem for the product of some partial sums

In this paper, we give the central limit theorem and almost sure central limit theorem for products of some partial sums of independent identically distributed random variables.     

独立随机序列最大值的几乎处处极限定理

本文研究了独立随机序列最大值分布的几乎必然收敛性.利用有关协方差的不等式和加权平均,获得独立随机序列最大值的几乎处处极限.将独立同分布随机序列的结论,推广了独立但不同分布的情形.     

An almost sure invariance principle for triangular arrays of banach space valued random variables

Summary We give a simpler proof of the probability invariance principle for triangular arrays of independent identically distributed random variables with values in a separable Banach space, recently proved by de Acosta [1], and improve this result to an almost sure invariance principle.     

On the harmonic averages of numerical sequences

In recent years, the almost sure central limit theorem attracted widespread attention in Probability Theory. It involves the harmonic (also called logarithmic) averages of a certain numerical sequence formed from a sequence of independent, identically distributed random variables. Our primary aim is to study the convergence behavior of the sequence of harmonic averages of a given numerical sequence from the viewpoint of Summability Theory. Received: 12 May 2005; revised: 1 July 2005     

The Convergence of the Sums of Independent Random Variables Under the Sub-linear Expectations

Let {Xn;n≥1} be a sequence of independent random variables on a probability space(Ω,F,P) and Sn=∑k=1n Xk.It is well-known that the almost sure convergence,the convergence in probability and the convergence in distribution of Sn are equivalent.In this paper,we prove similar results for the independent random variables under the sub-linear expectations,and give a group of sufficient and necessary conditions for these convergence.For proving the results,the Levy and Kolmogorov maximal inequalities for independent random variables under the sub-linear expectation are established.As an application of the maximal inequalities,the sufficient and necessary conditions for the central limit theorem of independent and identically distributed random variables are also obtained.     

Almost sure limit points of and the number of boundary crossings related to SLLN and LIL for record times,inter-record times and the number of record values

In this paper, the almost sure limit points and the moments of the number of boundary crossings of some functions of record times, inter-record times and the frequency of record values of a sequence of independent and identically distributed continuous random variables are studied.     

An almost sure central limit theorem for self-normalized products of sums of i.i.d. random variables

Let X,X₁,X₂,… be a sequence of independent and identically distributed positive random variables with EX=μ>0. In this paper we show that the almost sure central limit theorem for self-normalized products of sums holds only under the assumptions that X belongs to the domain of attraction of the normal law.     

Almost sure convergence of sums of maxima and minima of positive random variables

For a sequence of independent and identically distributed positive random variables, the almost sure convergence of sums of maxima (when suitably normalized) to appropriate constants is proved for both bounded and unbounded random variables. A similar result is also proved for sums of minima of such variables.     

鞅差序列加权和的几乎处处收敛(英文)

本文研究了一类鞅差序列加权和的收敛性的问题.利用一些基本不等式和截尾技术,获得了加权和的几乎处处收敛性,推广了关于独立同分布的随机变量序列的相关结果.