Strong convergence for weighted sums of WOD random variables and its application in the EV regression model
Applications of Mathematics, Tome 69 (2024) no. 1, pp. 93-111
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The strong convergence for weighted sums of widely orthant dependent (WOD) random variables is investigated. As an application, we further investigate the strong consistency of the least squares estimator in EV regression model for WOD random variables. A simulation study is carried out to confirm the theoretical results.
Classification :
60F15, 62F12
Keywords: errors-in-variables regression model; least squares estimator; widely orthant dependent; strong consistency
Keywords: errors-in-variables regression model; least squares estimator; widely orthant dependent; strong consistency
@article{10_21136_AM_2023_0004_23,
author = {Ding, Liwang and Jiang, Caoqing},
title = {Strong convergence for weighted sums of {WOD} random variables and its application in the {EV} regression model},
journal = {Applications of Mathematics},
pages = {93--111},
publisher = {mathdoc},
volume = {69},
number = {1},
year = {2024},
doi = {10.21136/AM.2023.0004-23},
language = {en},
url = {http://geodesic.mathdoc.fr/articles/10.21136/AM.2023.0004-23/}
}
TY - JOUR AU - Ding, Liwang AU - Jiang, Caoqing TI - Strong convergence for weighted sums of WOD random variables and its application in the EV regression model JO - Applications of Mathematics PY - 2024 SP - 93 EP - 111 VL - 69 IS - 1 PB - mathdoc UR - http://geodesic.mathdoc.fr/articles/10.21136/AM.2023.0004-23/ DO - 10.21136/AM.2023.0004-23 LA - en ID - 10_21136_AM_2023_0004_23 ER -
%0 Journal Article %A Ding, Liwang %A Jiang, Caoqing %T Strong convergence for weighted sums of WOD random variables and its application in the EV regression model %J Applications of Mathematics %D 2024 %P 93-111 %V 69 %N 1 %I mathdoc %U http://geodesic.mathdoc.fr/articles/10.21136/AM.2023.0004-23/ %R 10.21136/AM.2023.0004-23 %G en %F 10_21136_AM_2023_0004_23
Ding, Liwang; Jiang, Caoqing. Strong convergence for weighted sums of WOD random variables and its application in the EV regression model. Applications of Mathematics, Tome 69 (2024) no. 1, pp. 93-111. doi: 10.21136/AM.2023.0004-23
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