On complete convergence for widely orthant-dependent random variables and its applications in nonparametric regression models

Test ◽  
2014 ◽  
Vol 23 (3) ◽  
pp. 607-629 ◽  
Author(s):  
Xuejun Wang ◽  
Chen Xu ◽  
Tien-Chung Hu ◽  
Andrei Volodin ◽  
Shuhe Hu
Keyword(s):  
Nonparametric Regression ◽  
Regression Models ◽  
Complete Convergence ◽  
Random Variables ◽  
Dependent Random Variables ◽  
Widely Orthant Dependent

scholarly journals Complete convergence for weighted sums of widely orthant-dependent random variables

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Pingyan Chen ◽  
Soo Hak Sung
Keyword(s):  
Complete Convergence ◽  
Law Of Large Numbers ◽  
Random Variables ◽  
Weighted Sums ◽  
Dependent Random Variables ◽  
Strong Law ◽  
Link Type ◽  
Convergence Results ◽  
Large Numbers ◽  
Widely Orthant Dependent

AbstractThe complete convergence results for weighted sums of widely orthant-dependent random variables are obtained. A strong law of large numbers for weighted sums of widely orthant-dependent random variables is also obtained. Our results extend and generalize some results of Chen and Sung (J. Inequal. Appl. 2018:121, 2018), Zhang et al. (J. Math. Inequal. 12:1063–1074, 2018), Chen and Sung (Stat. Probab. Lett. 154:108544, 2019), Lang et al. (Rev. Mat. Complut., 2020, 10.1007/s13163-020-00369-5), and Liang (Stat. Probab. Lett. 48:317–325, 2000).

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