不同分布φ混合随机变量序列的强收敛性(英文)  

STRONG CONVERGENCE FOR φ-MIXING SEQUENCES OF RANDOM VARIABLES WITH NON-IDENTICALLY DISTRIBUTED

作　　者：黄海午[1,2] 王定成[1,3,4,5] 吴群英[2] 

机构地区：[1]电子科技大学数学科学学院,四川成都610054 [2]桂林理工大学理学院,广西桂林541004 [3]南京审计学院金融工程中心 [4]金融学院 [5]应用数学学院,江苏南京211815

出　　处：《数学杂志》2013年第2期221-227,共7页Journal of Mathematics

基　　金：Supported by the National Natural Science Foundation of China(11061012);the Program to Sponsor Teams for Innovation in the Construction of Talent Highlands in GuangxiInstitutions of Higher Learning;the Plan of Jiangsu Specially-Appointed Professors

摘　　要：本文研究了不同分布φ混合随机变量序列的强收敛性质的问题.利用φ混合随机变量序列的矩不等式和截尾的方法,获得了φ混合随机变量序列完全收敛性和几乎处处收敛性结果,所获得结果不仅推广了Baum和Katz(1965)关于独立同分布随机变量序列的结论,而且改进了Wu和Lin(2004)关于同分布混合随机变量序列的相关结论.In this article, we study the strong convergence properties of φ-mixing sequences of non-identically distributed random variables. By using the truncated method and the moment inequality of φ-mixing random variables, we obtain the complete convergence and almost sure convergence of φ-mixing sequences of random variables, which not only generalize and extend the corresponding results of Baum and Katz （1965） for independent and identically distributed random variables, but also improve the results of Wu and Lin （2004） for identically distributed φ-mixing sequences of random variables.

关 键 词：φ混合随机变量序列 完全收敛性 几乎处处收敛性 

分 类 号：O211.4[理学—概率论与数理统计]