相依的高斯及非负随机序列的强大数定律  

Strong Law of Large Numbers of Sequences of Dependent Gaussian and Nonnegative Random Variables

作　　者：袁代林[1] 赵联文[1] 刘赪[1] 

机构地区：[1]西南交通大学数学学院统计系,成都610031

出　　处：《应用概率统计》2016年第3期261-269,共9页Chinese Journal of Applied Probability and Statistics

基　　金：中央高校基本科研业务费专项基金(2682013CX037)资助

摘　　要：根据Alexander对具有正、负相协的随机变量序列满足强大数定律的条件,本文研究具有一般相依结构的高斯随机变量序列、非负随机变量序列以及一致有界随机变量序列,给出了其满足强大数定律的充分条件.最后给出了一个高斯序列满足强大数定律条件的例子.Examining the conditions of positively or negatively associated sequences of random variables obeying the strong law of large numbers provided by Alexander, the sequences of Gaussian random variables, nonnegative and uniformly bounded sequences of random variables with geueral dependent structure were studied, and the sufficient conditions for they obeying the strong law of large numbers were given. At last, an example for Gaussian sequence satisfying the strong law of large numbers was given.

关 键 词：高斯随机变量 非负随机变量 强大数定律 相依 

分 类 号：O212.4[理学—概率论与数理统计]