Geodesic
Complete moment convergence for weighted sums of widely orthant dependent random variables and its application in nonparametric regression model
Filomat, Tome 36 (2022) no. 8, p. 2761

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DOI

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.
DOI : 10.2298/FIL2208761Z
Classification : 60F15
Keywords: widely orthant dependent random variables, complete moment convergence, nonparametric regression model 
Aonan Zhang; Yawen Yu; Yan Shen. Complete moment convergence for weighted sums of widely orthant dependent random variables and its application in nonparametric regression model. Filomat, Tome 36 (2022) no. 8, p. 2761 . doi: 10.2298/FIL2208761Z
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     title = {Complete moment convergence for weighted sums of widely orthant dependent random variables and its application in nonparametric regression model},
     journal = {Filomat},
     pages = {2761 },
     year = {2022},
     volume = {36},
     number = {8},
     doi = {10.2298/FIL2208761Z},
     language = {en},
     url = {http://geodesic.mathdoc.fr/articles/10.2298/FIL2208761Z/}
}
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