Complete moment convergence for weighted sums of widely orthant dependent random variables and its application in nonparametric regression model

Aonan Zhang, Yawen Yu, Yan Shen


In this paper, the complete moment convergence of weighted sums for widely orthant dependent (WOD, in short) random variables are established. The results obtained in the paper generalize and improve some known ones. As an application of the main results, we present a result on complete consistency for the weighted estimator in a nonparametric regression model based on WOD errors.


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