NSD随机阵列最大加权和的矩收敛性及应用  

Moment Convergence for Maximum Weighted Sums of NSD Random Arrays and Application

作　　者：何其慧 HE Qihui(Department of Public Education,Anhui Finance and Trade Vocational College,Hefei 230601,China)

机构地区：[1]安徽财贸职业学院公共基础教学部,安徽合肥230601

出　　处：《通化师范学院学报》2024年第2期25-30,共6页Journal of Tonghua Normal University

基　　金：安徽省高等学校科学研究项目(2023AH040296)。

摘　　要：该文利用NSD随机阵列的极大值矩不等式研究了NSD随机阵列最大加权和的矩收敛性,相关定理改进且推广了已有关于AANA变量的结果 .此外,作为主要结果的应用,进一步研究了非参数回归模型加权估计量的矩相合性和弱相合性.This paper mainly investigates the moment convergence for the maximum weighted sums of an array of NSD random variables by using the maximum moment inequality of NSD random variables.The corresponding theorems improve and extend the existing result for AANA random variables.Moreover,as an application of the main results,the moment consistency and the weak consistency of the weighted esti-mator in nonparametric regression model are further investigated.

关 键 词：矩收敛性 最大加权和 NSD随机阵列 非参数模型 矩相合性 

分 类 号：O211.4[理学—概率论与数理统计]