φ混合序列的强大数律

讨论了不同分布φ混合序列的强大数律,推广了Kolmogorov强大数定律和Marcinkiewicz强大数定律.     

■混合序列的强大数律

讨论了不同分布■混合序列的强大数律,推广了Kolmogorov强大数定律和Marcinkiewicz强大数定律.     

混合序列加权和的强大数定律

设{Xn,n≥1}是同分布随机变量序列,{αnk,n≥1,1≤k≤n}是满足某种条件的常数序列.本文在ψ-混合,ρ-混合,ρ~-混合条件下讨论了加权和∑kn=1ankXk的Kolmogorov强大数定律.     

B值混合序列的一些收敛性结果

本文获得了B值ρ混合随机元序列的均值收敛性,Kolmogorov强大数定律以及正则和极大值矩的存在性问题,推广和改进了已有的结果.     

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.     

Kolmogorov统计量的精确分布及其在Bootstrap逼近中的应用

假设x₁,x_m iid服从分布F,当F连续时,Kolmogorov统计量的精确分布已由张里千(1956)获得.本文考虑在n个点上取概率为1/n的离散分布.得到的精确分布与张里千的结果有相同的形式.利用这个结果,得到Kolmogorov统计量分布的Bootstrap逼近的收敛速度为n^-1/2的阶.这是对统计量的极限分布形式复杂甚至未知的情况下Bootstrap逼近的收敛速度问题的一个初步的探讨.     

稳健Bayes估计

在Bayes估计问题中,我们证明了当损失函数满足一定条件时,所对应的Bayes估计是稳健的:即Bayes估计是后验分布的连续泛函(相对于后验分布之间的Kolmogorov距离)。     

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.     

Lotka-Volterra系统与Kolmogorov系统极限环的存在性与中心焦点的算法化判定[英文]

本文得到Kolmogorov系统为中心的充分条件.对三维Lotka-Volterra系统和Kolmogorov系统之间的关系进行探讨.通过研究Kolmogorov系统极限环的存在性,得到三维Lotka-Volterra系统极限环的存在性.     

Markov预解式之分解与Kolmogorov Q过程之精析

本文应用预解算子的分解定理来研究带有限个瞬时态的Kolmogorov Q-矩阵.此模型是Kolmogorov等人早期研究的一类Q-矩阵的推广.但本文的讨论不限于存在唯一性,而是更着重于对过程性质的深刻分析.在给出一个极易验证的存在唯一性条件后,本文证明Kolmogorov Q-过程必定是常返的.一个非常好的过程遍历的充分必要条件也在本文给出.在此过程遍历的条件下,过程极限分布的简洁清晰的显式也被展示出来.过程的可逆性问题也在本文中获得了很好的完备解答.     

两两NQD列大数定律的一个注记

利用两两NQD列三级数定理的思想和Chebyshev不等式,研究了两两NQD列在一类广泛条件下的弱大数定律和一类加强条件下的强大数定律,得到了与独立情形一致的结果,还特别讨论了同分布情形,推广了相关文献的结果．     

Strong Limit Theorems for Increments of Sums of Independent Random Variables

We derive universal strong laws for increments of sums of independent, nonidentically distributed, random variables. These results generalize universal results of the author for the i.i.d. case which include the strong law of large numbers, law of the iterated logarithm, Erdos-Renyi law, and Csorgo-Revesz laws. Bibliography: 27 titles. __________ Translated from Zapiski Nauchnykh Seminarov POMI, Vol. 311, 2004, pp. 260–285.     

EQUIVALENCE OF COMPLETE CONVERGENCE AND LAW OF LARGE NUMBERS FOR B-VALUED RANDOM ELEMENTS

1.IntroductionandMainResultsAsequence{X.,n21}ofrealvaluedrandomvariablesissaidtosatisfythelawoflargenumbersofHsu-Robbins(1947)typewithasequence{b.}ofrealnumbersifVP(ISn-b.I2ne)< co,Ve>0,(1.1)ZP(ISn-b.I2ne)< co,Ve>0,(1.1)n=1whereS.~ZXi.Conditionsunderwhich(1.1)holdswerediscussedinmanypapers.Ai=1moregeneralresultforlidrealvaluedrandomvariablesisgivenin[2].LetBbearealseparableBanachspacewithnorm11'11and{X.}asequenceofB-valuedrandomelemefltsandputSa~ZXi,n21.Candcdenotepositivefinitecon…     

两两独立同分布序列Cesàro强大数定律的收敛速度

设{X,Xn,n≥0}是两两独立同分布的随机变量序列,11．为了证明这一结论而获得到的两两负相关随机变量序列的Cesaro强大数定律收敛速度的结果本身也是有意义的．此结果对于同分布的两两NQD序列也是对的．     

EQUIVALENCE OF COMPLETE CONVERGENCE AND LAW OF LARGE NUMBERS FOR B-VALUED RANDOM ELEMENTS＇

Under some conditions on probability, this note discusses the equivalence between the complete convergence and the law of large number forB- valued independent random elements. The results of [10] become a simple corollary of the results here. At the same time, the author uses them to investigate the equivalence of strong and weak law of large numbers, and there exists an example to show that the conditions on probability are weaker. Project supported by the National Natural Science Foundation of China.     

Strong Laws of Large Numbers for Sublinear Expectation under Controlled 1st Moment Condition

This paper deals with strong laws of large numbers for sublinear expectation under controlled 1st moment condition. For a sequence of independent random variables, the author obtains a strong law of large numbers under conditions that there is a control random variable whose 1st moment for sublinear expectation is finite. By discussing the relation between sublinear expectation and Choquet expectation, for a sequence of i.i.d random variables, the author illustrates that only the finiteness of uniform 1st moment for sublinear expectation cannot ensure the validity of the strong law of large numbers which in turn reveals that our result does make sense.     

一类马尔可夫骨架过程的强大数定律和中心极限定理

基于马尔可夫骨架过程极限分布的已有研究结果,本文运用波莱尔-康特立引理、更新理论、科尔莫哥洛夫的强大数定律以及独立同分布情形的中心极限定理等重要理论,分别给出了一类马尔可夫骨架过程对应的累积过程满足强大数定律和中心极限定理的充分条件.     

Convergence Rates in the Law of Large Numbers under Sublinear Expectations

In this note, we study convergence rates in the law of large numbers for independent and identically distributed random variables under sublinear expectations. We obtain a strong L^p-convergence version and a strongly quasi sure convergence version of the law of large numbers.     

Kolmogorov's strong law of large numbers for fuzzy random variables

In this paper, Kolmogorov's strong law of large numbers for sums of independent and level-wise identically distributed fuzzy random variables is obtained.     

Strong laws of large numbers for sub-linear expectations

We investigate three kinds of strong laws of large numbers for capacities with a new notion of independently and identically distributed(IID) random variables for sub-linear expectations initiated by Peng.It turns out that these theorems are natural and fairly neat extensions of the classical Kolmogorov’s strong law of large numbers to the case where probability measures are no longer additive. An important feature of these strong laws of large numbers is to provide a frequentist perspective on capacities.