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Journal of Systems Science and Complexity

, Volume 30, Issue 5, pp 1160–1172 | Cite as

A relative error estimation approach for multiplicative single index model

  • Zhanfeng WangEmail author
  • Zimu Chen
  • Yaohua Wu
Article

Abstract

As an alternative to absolute error methods, such as the least square and least absolute deviation estimations, a product relative error estimation is proposed for a multiplicative single index regression model. Regression coefficients in the model are estimated via a two-stage procedure and their statistical properties such as consistency and normality are studied. Numerical studies including simulation and a body fat example show that the proposed method performs well.

Keywords

Asymptotic properties least product relative error relative errors single index model 

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Copyright information

© Institute of Systems Science, Academy of Mathematics and Systems Science, CAS and Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  1. 1.Department of Statistics and Finance, School of ManagementUniversity of Science and Technology of ChinaHefeiChina

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