Strong Law of Large Numbers for Array of Rowwise AANA Random Variables

In this article, the strong laws of large numbers for array of rowwise asymptotically almost negatively associated（AANA） random variables are studied. Some sufficient conditions for strong laws of large numbers for array of rowwise AANA random variables are presented without assumption of identical distribution. Our results extend the corresponding ones for independent random variables to case of AANA random wriables.     

Laws of Large Numbers for Exchangeable Random Sets in Kuratowski-Mosco Sense

Abstract

Most of the results for laws of large numbers based on Banach space valued random sets assume that the sets are independent and identically distributed (IID) and compact, in which Rådström embedding or the refined method for collection of compact and convex subsets of a Banach space plays an important role. In this paper, exchangeability among random sets as a dependency, instead of IID, is assumed in obtaining strong laws of large numbers, since some kind of dependency of random variables may be often required for many statistical analyses. Also, the Hausdorff convergence usually used is replaced by another topology, Kuratowski-Mosco convergence. Thus, we prove strong laws of large numbers for exchangeable random sets in Kuratowski-Mosco convergence, without assuming the sets are compact, which is weaker than Hausdorff sense.     

�������������������������������ʼ���ǿ��������

Strong laws of large numbers play key role in nonadditive probability theory. Recently, there are many research papers about strong laws of large numbers for independently and identically distributed (or negatively dependent) random variables in the framework of nonadditive probabilities (or nonlinear expectations). This paper introduces a concept of weakly negatively dependent random variables and investigates the properties of such kind of random variables under a framework of nonadditive probabilities and sublinear expectations. A strong law of large numbers is also proved for weakly negatively dependent random variables under a kind of sublinear expectation as an application     

NA随机变量列一类强大数律的充分必要条件

本文给出了具有不同分布NA随机变量列满足一类强大数律的充分必要条件, 从而将Egorov对独立随机变量列建立的结果推广到NA随机变量情形; 作为应用, 我们还建立了一个新的强大数律.     

NOD随机变量加权和的极限

The strong laws of large numbers and laws of the single logarithm for weighted sums of NOD random variables are established.The results presented generalize the corresponding results of Chen and Gan [5] in independent sequence case.     

随机变量的截尾与任意随机变量序列的强极限定理

利用随机变量的截尾研究任意随机变量序列的性质,建立了一类矩条件下任意随机变量序列的强极限定理.作为推论,得到了可列非齐次马尔可夫过程的一个强极限定理,推广了鞅差序列当1≤p≤2和p≥2时的Chow定理,相应的一些已有结果和若干经典的关于独立随机变量序列的强大数定律是本文的特例。     

On Almost Sure Behavior of Sums of Independent Banach Space Valued Random Variables

Levy's strong law of large numbers is extended to the Banach space and Chover type laws of the iterated logarithm are proved for random variables which do not necessarilly belong to the domain of normal attraction of a stable law. Also characterizations of Banach spaces in which conditions on the summands imply the above strong laws are given.     

分块m-负相依随机变量的Wittmann 型强大数律

本文得到了分块m-负相依随机变量的Wittmann 型强大数律,这些结果推广和改进了已知的一些文献中相关的结论.     

The Law of Large Numbers and the Ito-Nisio Theorem for Vector Valued Random Fields

Strong convergence results are obtained for vector-valued random fields. Substantial development of Banach-valued random fields and summability results is needed to provide the framework for the major results since many plausible extensions fail for multi-indexed Banach-valued random variables. This development yields general convergence results for random fields in Banach spaces, including an Ito-Nisio theorem and strong laws of large numbers.     

NA随机变量加权和的极限结果

该文研究了NA随机变量序列加权和的Marcinkiewcz Zygmund 强大数定律和完全收敛性.这些结果推广和完善了Bai和Cheng[1]和Cuzick[2]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.     

同分布的NA序列加权和的强大数律

讨论了同分布NA随机变量序列加权和的强大数律,所得结果推广了Z．D．Bai和P．E．Cheng及S．H．Sung的结果．     

关于~*-mixing随机变量序列的强大数定律

利用任意随机变量序列的强大数定律讨论 * -mixing随机变量序列的强大数定律 ,得到了该序列的一个强极限定理 ,推广了经典的 * mixing随机变量序列的强大数定律 .同时讨论了 m相依序列和独立随机变量序列的强大数定律 .     

Strong Law of Large Numbers for Stationary Sequences of Random Upper Semicontinuous Functions

Abstract

The strong laws of large numbers with the convergence in the sense of the uniform Hausdorff metric for stationary sequences of random upper semicontinuous functions is established. This approach allows us to deduce many results on the convergence in uniform Hausdorff metric of random upper semicontinuous functions from the relevant results on real-valued random variables that appear as their support functions.     

Strong Laws for Blockwise ℳ-Dependent Random Fields

We consider random fields and introduce a concept of ℳ-dependence for random fields. Using a lemma from summability theory we prove strong laws of large numbers for blockwise ℳ-dependent random fields under various moment conditions, thereby generalizing some results in the literature from independent random fields. This research was started while the first author visited the University of Ulm, Institute of Number Theory & Probability Theory in October 2006; and it was also supported by the Hungarian National Foundation for Scientific Research under Grant T 046192.     

\rho混合随机变量的强大数律

In this paper we present some results for the general strong laws of large numbers of ■-mixing random variables by a maximal inequality of Utev and Peligrad.These results extend and improve the related known works in the literature.     

Asymptotic Behavior of Increments of Random Fields

We derive universal strong laws for increments of sums of i.i.d. random variables with multidimensional indices without an exponential moment. Our theorems yield the strong law of large numbers, the law of the iterated logarithm, and the Csorgo-Revesz laws for random fields. New results are obtained for distributions from domains of attraction of the normal law and of completely asymmetric stable laws with index (1, 2). Bibliography: 18 titles.__________Translated from Zapiski Nauchnykh Seminarov POMI, Vol. 298, 2003, pp. 191–207.     

$B$值独立随机元序列加权和的完全收敛性和强大数律

In this paper, we obtain theorems of complete convergence and strong laws of large numbers for weighted sums of sequences of independent random elements in a Banach space of type p （1 ≤ p ≤ 2）. The results improve and extend the corresponding results on real random variables obtained by [1] and [2].     

直线上随机环境中可逗留的随机游动的若干性质

主要研究直线上随机环境中可逗留的随机游动的常返性与极限性质,在独立随机环境下,通过强大数定律给出了常返与暂留的一个充分条件;在一般随机环境下,通过数列的有界性给出了常返与零常返的充分条件并讨论了在独立随机环境下非常返性中的大数定律,从而推广了Solomon的研究框架.     

混合序列部分和的强大数定律

设{Xn，n≥1）是ρ^-混合序列．利用随机变量的截尾方法和ρ^-混合序列的三级数定理这一工具研究了ρ^-混合序列的性质。得到了矩条件下ρ^-混合序列的—类强极限定理和强大数定律。并给出了一些简单应用。推广了若干经典的强大数定律．