NSD随机变量随机加权和的完全矩收敛性

IF 0.8 4区数学

数学研究 Pub Date : 2019-06-01 DOI:10.4208/JMS.V52N1.19.03

xiangmin Sun

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引用次数: 0

摘要

本文研究了负超加性相依随机变量随机加权和的完全矩收敛性和完全收敛性。本文的结果将常加权和的收敛定理推广到因随机变量的随机加权和。此外，还得到了NSD序列的强数定律。AMS受试者分类：60F15。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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On Complete Moment Convergence for Randomly Weighted Sums of NSD Random Variables

In this paper, we investigate the complete moment convergence and complete convergence for randomly weighted sums of negatively superadditive dependent (NSD, in short) random variables. The results obtained in the paper generalize the convergence theorem for constant weighted sums to randomly weighted sums of dependent random variables. In addition, strong law of large numbers for NSD sequence is obtained. AMS subject classifications: 60F15.

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来源期刊

数学研究 MATHEMATICS-

自引率

0.00%

发文量

1109

期刊介绍： Journal of Mathematical Study (JMS) is a comprehensive mathematical journal published jointly by Global Science Press and Xiamen University. It publishes original research and survey papers, in English, of high scientific value in all major fields of mathematics, including pure mathematics, applied mathematics, operational research, and computational mathematics.