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THE CONSISTENCY FOR THE WEIGHTED ESTIMATOR OF NON-PARAMETRIC REGRESSION MODEL BASED ON WIDELY ORTHANT-DEPENDENT ERRORS

Published online by Cambridge University Press:  03 July 2017

Hao Xia
Affiliation:
School of Mathematical Sciences, Anhui University, Hefei 230601, People's Republic of China E-mail: 2943004220@qq.com; wuyi8702@163.com; 715231263@qq.com; wxjahdx2000@126.com
Yi Wu
Affiliation:
School of Mathematical Sciences, Anhui University, Hefei 230601, People's Republic of China E-mail: 2943004220@qq.com; wuyi8702@163.com; 715231263@qq.com; wxjahdx2000@126.com
Xinran Tao
Affiliation:
School of Mathematical Sciences, Anhui University, Hefei 230601, People's Republic of China E-mail: 2943004220@qq.com; wuyi8702@163.com; 715231263@qq.com; wxjahdx2000@126.com
Xuejun Wang
Affiliation:
School of Mathematical Sciences, Anhui University, Hefei 230601, People's Republic of China E-mail: 2943004220@qq.com; wuyi8702@163.com; 715231263@qq.com; wxjahdx2000@126.com

Abstract

In this paper, the complete consistency for the weighted estimator of non-parametric regression model based on widely orthant-dependent errors is established, where the restriction imposed on the dominating coefficient g(n) is very general. Moreover, under some stronger moment condition, we further obtain the convergence rate of the complete consistency, where the assumption on the dominating coefficient g(n) is also very general.

Type
Research Article
Copyright
Copyright © Cambridge University Press 2017 

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