On exact strong laws of large numbers under general dependence conditions

IF 0.4 4区 数学 Q4 STATISTICS & PROBABILITY
A. Adler, P. Matuła
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引用次数: 14

Abstract

We study the almost sure convergence of weighted sums of dependent random variables to a positive and finite constant, in the case when the random variables have either mean zero or no mean at all. These are not typical strong laws and they are called exact strong laws of large numbers. We do not assume any particular type of dependence and furthermore consider sequences which are not necessarily identically distributed. The obtained results may be applied to sequences of negatively associated random variables.
关于一般依赖条件下的精确强大数定律
我们研究了在随机变量的均值为零或根本没有均值的情况下,相依随机变量的加权和几乎肯定收敛于正的有限常数。这些不是典型的强定律,它们被称为大数的精确强定律。我们不假设任何特定类型的依赖性,并且进一步考虑不一定相同分布的序列。所获得的结果可以应用于负相关随机变量的序列。
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来源期刊
CiteScore
0.70
自引率
0.00%
发文量
0
审稿时长
>12 weeks
期刊介绍: PROBABILITY AND MATHEMATICAL STATISTICS is published by the Kazimierz Urbanik Center for Probability and Mathematical Statistics, and is sponsored jointly by the Faculty of Mathematics and Computer Science of University of Wrocław and the Faculty of Pure and Applied Mathematics of Wrocław University of Science and Technology. The purpose of the journal is to publish original contributions to the theory of probability and mathematical statistics.
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