WOD随机变量序列加权和完全收敛性及其应用  

Complete convergence for weighted sums of WOD randomvariable sequence and its application

作　　者：张玉 ZHANG Yu(School of Mathematics and Big Data,Chaohu University,Hefei 238024,China)

机构地区：[1]巢湖学院数学与大数据学院,安徽合肥238024

出　　处：《湖北大学学报（自然科学版）》2023年第5期695-701,共7页Journal of Hubei University：Natural Science

基　　金：巢湖学院校级项目(XLY-202104);巢湖学院重点建设学科项目(kj22zdjsxk01)资助

摘　　要：随机变量序列是概率极限理论重要研究的内容,由于随机变量序列独立的条件已经不满足日常生活和科学研究的实际要求,相依随机变量序列被提出.其在风险预测、地质勘测、保险等领域应用非常广泛,宽相依(widely orthant dependent, WOD)随机变量序列是一种常见的相依随机变量序列.采用随机变量尾截技术,结合运用新的矩不等式证明研究WOD随机变量序列加权和完全收敛性,且将其结果应用到非参数估计当中具有重要意义.As everyone knows random variable sequence is an important research content of probability limit theory.Because the independent condition of random variable sequence has not met the actual requirements of daily life and scientific research,dependent random variable sequence has been proposed.It is widely used in risk prediction,geological survey,insurance and other fields.Widely orthant dependent WOD(widely orthant dependent)random variable sequence is a common dependent random variable sequence.It is of great significance to study the complete convergence of weighted sums of WOD random variable sequences by using the tail cut technique of random variables and new moment inequalities proof,and to apply its results to nonparametric estimation.

关 键 词：WOD 完全收敛性 非参数估计 随机变量尾截 

分 类 号：O211.4[理学—概率论与数理统计]