JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE) ›› 2015, Vol. 50 ›› Issue (04): 20-23.doi: 10.6040/j.issn.1671-9352.0.2014.043

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Maximum empirical likelihood estimation in nonlinear semiparametric regression models with missing data

WU Da-yong1, LI Feng2   

  1. 1. Department of Mathematics and Physics, Zhengzhou Institute of Aeronautical Industry Management, Zhengzhou 450015, Henan, China;
    2. Faculty of Trade and Economics, Zhengzhou Institute of Aeronautical Industry Management, Zhengzhou 450015, Henan, China
  • Received:2014-02-20 Revised:2014-09-24 Online:2015-04-20 Published:2015-04-17

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Abstract: The linear semiparametric regression models with missing data were considered. The maximum empirical estimations of the regression coefficients, and the smoothing function were obtained by the maximum empirical method. The asymptotic normality and consistency of the proposed estimations were proved under some appropriate conditions.

Key words: nonlinear semiparametric regression models, missing data, empirical likelihood, asymptotic normality, consistency

CLC Number: 

  • O212
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