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ON CONSISTENCY OF LS ESTIMATORS IN THE ERRORS-IN-VARIABLE REGRESSION MODEL

Published online by Cambridge University Press:  01 December 2016

Xuejun Wang,
Mengmei Xi,
Hongxia Wang and
Shuhe Hu
Xuejun Wang
Affiliation:
School of Mathematical Sciences, Anhui University, Hefei 230601, People's Republic of China E-mail: wxjahdx2000@126.com
Mengmei Xi
Affiliation:
School of Mathematical Sciences, Anhui University, Hefei 230601, People's Republic of China E-mail: wxjahdx2000@126.com
Hongxia Wang
Affiliation:
Department of Statistics, Nanjing Audit University, Nanjing 211815, People's Republic of China
Shuhe Hu
Affiliation:
School of Mathematical Sciences, Anhui University, Hefei 230601, People's Republic of China
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Abstract

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Under some mild conditions, the strong consistency and complete consistency of the LS estimators in the errors-in-variable regression model with weakly negative dependent errors are obtained, which generalize the corresponding ones for negatively associated random variables. In addition, the simulation study shows that the biases of our method are small, and our method performs well.

Keywords

complete consistencyEV regression modelstrong consistencyweakly negative dependent random variables

Information

Type
Research Article
Information
Probability in the Engineering and Informational Sciences , Volume 32 , Issue 1 , January 2018, pp. 144 - 162
Copyright
Copyright © Cambridge University Press 2016 

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