Complete moment convergence for m-END random variables with application to non-parametric regression models

2020 ◽  
pp. 1-23
Author(s):  
Nan Cheng ◽  
Xiaoqin Li ◽  
Minghui Wang ◽  
Xuejun Wang ◽  
Mengmei Xi
Keyword(s):  
Regression Models ◽  
Random Variables ◽  
Complete Moment Convergence ◽  
Parametric Regression ◽  
Moment Convergence ◽  
End Random Variables ◽  
Parametric Regression Models ◽  
Non Parametric

COMPLETE MOMENT CONVERGENCE FOR ARRAYS OF ROWWISE NEGATIVELY ASSOCIATED RANDOM VARIABLES AND ITS APPLICATION IN NON-PARAMETRIC REGRESSION MODEL

2017 ◽  
Vol 32 (1) ◽  
pp. 37-57 ◽  
Author(s):  
Yi Wu ◽  
Xuejun Wang ◽  
Soo Hak Sung
Keyword(s):  
Numerical Simulation ◽  
Regression Model ◽  
Random Variables ◽  
Complete Moment Convergence ◽  
Parametric Regression ◽  
Associated Random Variables ◽  
Negatively Associated ◽  
Complete Consistency ◽  
Moment Convergence ◽  
Non Parametric

In this paper, some results on the complete moment convergence for arrays of rowwise negatively associated (NA, for short) random variables are established. The results obtained in this paper correct the corresponding one obtained in Ko [13] and also improve and generalize the corresponding ones of Kuczmaszewska [14] and Ko [13]. As an application of the main results, we present a result on complete consistency for the estimator in a non-parametric regression model based on NA errors. Finally, we provide a numerical simulation to verify the validity of our result.

Using linear and non-parametric regression models to describe the contribution of non-linear loads on the voltage harmonic distortions in the electrical grid

2016 ◽  
Vol 10 (8) ◽  
pp. 1825-1832 ◽  
Author(s):  
Edson Ortiz de Matos ◽  
Allan Rodrigo Arrifano Manito ◽  
Ubiratan Holanda Bezerra ◽  
Benjamim Cordeiro Costa ◽  
Thiago Mota Soares ◽  
...  
Keyword(s):  
Regression Models ◽  
Parametric Regression ◽  
Electrical Grid ◽  
Non Linear ◽  
Parametric Regression Models ◽  
Harmonic Distortions ◽  
Non Parametric

Complete convergence and complete moment convergence for extended negatively dependent random variables

Filomat ◽  
2017 ◽  
Vol 31 (5) ◽  
pp. 1381-1394 ◽  
Author(s):  
Aiting Shen ◽  
Yu. Zhang ◽  
Wenjuan Wang
Keyword(s):  
Complete Convergence ◽  
Type Inequality ◽  
Random Variables ◽  
Weighted Sums ◽  
Complete Moment Convergence ◽  
Moment Inequalities ◽  
Dependent Random Variables ◽  
Moment Convergence ◽  
Negatively Dependent Random Variables ◽  
End Random Variables

In this paper, we provide some probability and moment inequalities (especially the Marcinkiewicz-Zygmund type inequality) for extended negatively dependent (END, in short) random variables. By using the Marcinkiewicz-Zygmund type inequality and the truncation method, we investigate the complete convergence for sums and weighted sums of arrays of rowwise END random variables. In addition, the complete moment convergence for END random variables is obtained. Our results generalize and improve the corresponding ones of Wang et al. [18] and Baek and Park [2].

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