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Probability in the Engineering and Informational Sciences Probability in the Engineering and Informational Sciences

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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 ,
Yi Wu ,
Xinran Tao  and
Xuejun Wang
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
Corresponding
E-mail address:
2943004220@qq.com
wuyi8702@163.com
715231263@qq.com
wxjahdx2000@126.com
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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.

Keywords

complete consistency convergence rate non-parametric regression model weighted estimator widely orthant-dependent errors
Type
Research Article
Information
Probability in the Engineering and Informational Sciences , Volume 32 , Issue 3 , July 2018 , pp. 469 - 481
Copyright
Copyright © Cambridge University Press 2017 

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