Strong laws for weighted sums of some dependent random variables and applications

被引:1
|
作者
Du, Menghuan [1 ]
Miao, Yu [1 ,2 ]
机构
[1] Henan Normal Univ, Coll Math & Informat Sci, Xinxiang 453007, Henan, Peoples R China
[2] Henan Normal Univ, Henan Engn Lab Big Data Stat Anal & Optimal Contro, Xinxiang 453007, Henan, Peoples R China
基金
中国国家自然科学基金;
关键词
Marcinkiewicz-Zygmund type strong laws; weighted sums; linear EV regression models; LS estimators; strong consis-tency; widely orthant dependent random variables; LS ESTIMATOR; COMPLETE CONVERGENCE; SURE CONVERGENCE; INEQUALITIES; THEOREM; CONSISTENCY;
D O I
10.2298/FIL2318161D
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
Let {Xn, n >= 1} be a sequence of random variables satisfying a generalized Rosenthal type inequality and stochastically dominated by a random variable X. Let {ani, 1 <= i <= n, n >= 1} be an array of constants. We study the Marcinkiewicz-Zygmund type strong laws for weighted sums sigma ni=1 aniXi under the condition that the exponential moment of the random variable X exists. These results are the interesting supplements for some known results. As statistical applications, we provide the strong consistency of LS estimators in simple linear EV regression models with widely orthant dependent random errors.
引用
收藏
页码:6161 / 6176
页数:16
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