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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: [email protected]; [email protected]; [email protected]; [email protected]
Yi Wu
Affiliation:
School of Mathematical Sciences, Anhui University, Hefei 230601, People's Republic of China E-mail: [email protected]; [email protected]; [email protected]; [email protected]
Xinran Tao
Affiliation:
School of Mathematical Sciences, Anhui University, Hefei 230601, People's Republic of China E-mail: [email protected]; [email protected]; [email protected]; [email protected]
Xuejun Wang
Affiliation:
School of Mathematical Sciences, Anhui University, Hefei 230601, People's Republic of China E-mail: [email protected]; [email protected]; [email protected]; [email protected]
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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 consistencyconvergence ratenon-parametric regression modelweighted estimatorwidely 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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