负相关随机变量序列加权和的完全收敛性

Y. Kolani, A. Gning, S. Diouf
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引用次数: 0

摘要

本文是对部分和的完全收敛性的理论贡献。让 $\lbrace X_n, n \geq 1 \rbrace$ 是一个非负依赖随机序列,它由随机变量 $X$ 和 $\lbrace \Psi_{ni} ; 1\leq i \leq n, n \geq 1 \rbrace $ 是一个随机变量数组。在温和条件下,我们建立了加权和 $\sum_{i=1}^j \Psi_{ni}X_i $ 的完全收敛性。 这个用随机系数得到的结果推广了用实系数得到的结果 [12-14,16]。我们的结果还将之前从独立同分布情况下获得的完全收敛定理推广到了负相关情况下。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
COMPLETE CONVERGENCE FOR WEIGHTED SUMS OF SEQUENCES OF NEGATIVELY DEPENDENT RANDOM VARIABLES
This paper is a theoretical contribution on the complete convergence of partial sums. Let $ \lbrace X_n, n \geq 1 \rbrace$ be a sequence of non negatively dependent random, which is stochastically dominated by a random variable $X$ and $\lbrace \ \Psi_{ni} ; 1\leq i \leq n, n\geq 1\rbrace $ be a an array of random variables. Under mild condition we establish the complete convergence for weighted sums $\sum_{i=1}^j \Psi_{ni}X_i $. This result obtained with random coefficients generalizes the work of those obtained with real coefficients [12-14,16]. Our results also generalize those on complete convergence theorem previously obtained from the independent and identically distributed case to negatively dependent.
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