锁定固定治疗老年肱骨髁间骨折31例分析

利用截尾的方法和负相关(ND)随机变量的矩不等式,研究ND随机变量序列加权和的完全收敛性,结果,我们把独立同分布随机变量序列的完全收敛性定理推广到了ND序列情形下成立.     

ND随机变量序列加权和的完全收敛性(英文)

利用截尾的方法和负相关(ND)随机变量的矩不等式,研究ND随机变量序列加权和的完全收敛性,结果,我们把独立同分布随机变量序列的完全收敛性定理推广到了ND序列情形下成立.     

非平稳ND序列部分和的精确渐近性

利用中心极限定理和概率不等式,本文建立了非平稳ND序列部分和的精确渐近性,得到了与非平稳NA序列情形下相同的结果.     

关于“对数和”不等式在信息论中应用的一个注记

利用对数和不等式,在一般情形下证明了信息论中的两个基本定理,由此指出有关教材相应方法的局限性并给予了推广.     

局部广义高斯序列的若干新结果

给出了局部广义高斯序列部分和的一类绝对矩不等式及大偏差,并利用这些不等式证明了局部广义高斯序列的大数定律,同时建立了局部广义高斯序列的重对数收敛速度.     

NA随机变量序列的最大部分和不等式及有界重对数律

本文给出了NA随机变量序列关于最大部分和的概率不等式及矩不等式,并获得了NA随机变量序列的Teicher型和Egorov型有界重对数律等.     

鞅差序列的Bernstein型不等式及其应用

本文将独立随机变量序列的Bernstein型不等式推广到鞅差序列情形,给出该不等式的一个应用,并在一定条件下证明了非参数回归中函数估计的强相合性.     

加权U—统计量的一个重对数律

证明了关于独立同分布随机变量序列的加权Ｕ－统计量的一个重对数律,类似于献「３」证明了一个加权Ｕ－统计量的解耦不等式。     

不同分布WOD随机变量序列的重对数律

在一个独立随机变量序列的重对数律的基础上,获得了一个不同分布WOD随机变量序列的重对数定理,定理的证明基于一个Kolmogorov型指数不等式.     

无界函数指标集上经验过程大偏差的局部概率不等式及应用

提出并研究了无界函数指标集合上经验过程的大偏差尾部的局部概率指数不等式, 给出了一种新的截割原始概率空间的方法和新的对称化方法. 利用这些方法, 导出了无界函数指标集合上非i.i.d.独立样本的经验过程大偏差尾部的局部概率指数不等式, 并给出了它们的若干应用. 作为应用的一个附带结果, 在Kolmogorov定理所给的条件下, 将Kolmogorov关于非i.i.d的独立随机变量和的强收敛结果推广到无界函数指标集上的经验过程情形, 并且得到了无界函数指标集上经验过程大偏差尾部的局部概率指数不等式和对数律.     

Exponential inequalities under the sub-linear expectations with applications to laws of the iterated logarithm

Kolmogorov’s exponential inequalities are basic tools for studying the strong limit theorems such as the classical laws of the iterated logarithm for both independent and dependent random variables. This paper establishes the Kolmogorov type exponential inequalities of the partial sums of independent random variables as well as negatively dependent random variables under the sub-linear expectations. As applications of the exponential inequalities, the laws of the iterated logarithm in the sense of non-additive capacities are proved for independent or negatively dependent identically distributed random variables with finite second order moments. For deriving a lower bound of an exponential inequality, a central limit theorem is also proved under the sub-linear expectation for random variables with only finite variances.     

β混合随机变量序列加权和的收敛性

本文研究了混合随机变量序列加权和的收敛性.利用Utev, S.和Peligrad, M不等式得到了混合随机变量序列加权和的收敛性定理及Hajeck-Rènyi型不等式,推广和改进了W.F,Stout,吴群英,J.Hajeck和A.Rènyi.的相应结论.     

Almost sure convergence theorem and strong stability for weighted sums of NSD random variables

In this paper, Kolmogorov-type inequality for negatively superadditive dependent (NSD) random variables is established. By using this inequality, we obtain the almost sure convergence for NSD sequences, which extends the corresponding results for independent sequences and negatively associated (NA) sequences. In addition, the strong stability for weighted sums of NSD random variables is studied.     

Some Convergence Properties for ψ-Mixing Sequences

In this paper,we extend the Kolmogorov-type inequality to the case of ψ-mixing sequences.Moreover,we study the strong limit theorems for partial sums of ψ-mixing random variables.As a result,we extend the Khintchine-Kolmogorov-type convergence theorem,the three series theorem,Marcinkiewicz strong law of large number to the case of ψ-mixing sequences.     

$\psi$混合序列的一些收敛性质

In this paper,we extend the Kolmogorov-type inequality to the case of ψ-mixing sequences.Moreover,we study the strong limit theorems for partial sums of ψ-mixing random variables.As a result,we extend the Khintchine-Kolmogorov-type convergence theorem,the three series theorem,Marcinkiewicz strong law of large number to the case of ψ-mixing sequences.     

φ-混合随机变量序列收敛性质的若干新结果

本文将Kolmogorov型不等式推广到φ-混合序列,并且研究其强收敛性质,得到了φ-混合序列的Khintchine-Kolmogorov型收敛定理、三级数定理和Marcitlkiewicz型强大数定律.     

基于EV模型ND样本加权和的相合性

本文研究变系数EV模型的ND样本加权和的相合性问题.利用ND序列的Bernstein型不等式和截尾的方法,获得了ND样本加权和sum from i=1 to n(W_(ni)(t_0)Y_i)的强、弱相合性,推广了独立随机变量加权和的相合性.     

Strong near-epoch dependence

We introduce a new class of dependent sequences of random variables, which is a subclass of near-epoch dependent sequences, but can also be approximated by mixing sequences. For this kind of sequences of random variables, we call them strong near-epoch dependent sequences, ap-order,p > 2, (maximum) moment inequality is established under weaker dependence sizes.     

相依随机变量阵列加权和的矩完全收敛性

本文研究了相依随机变量阵列加权和的矩完全收敛性.利用矩不等式和截尾法,建立了相依随机变量阵列加权和的矩完全收敛性的充分条件.将Volodin等(2004)及陈平炎等(2006)的关于独立随机变量阵列的结果推广到了负相协和负相依随机变量阵列的情形,推广并完善了Sung(2011),吴群英(2012)及郭明乐和祝东进(2012)的结果.     

Equivalent Conditions of Complete qth Moment Convergence for Weighted Sums of Sequences of Negatively Orthant Dependent Random Variables

In this paper, the complete qth moment convergence for weighted sums of sequences of negatively orthant dependent random variables is investigated. By applying moment inequality and truncation methods, the equivalent conditions of complete qth moment convergence for weighted sums of sequences of negatively orthant dependent random variables are established. These results not only extend the corresponding results obtained by Li and Sp\v{a}taru\ucite{4}, Liang et al.\ucite{5}, Guo\ucite{6} and Gut\ucite{21} to sequences of negatively orthant dependent random variables, but also improve them.