Acta mathematica scientia,Series A ›› 2009, Vol. 29 ›› Issue (5): 1338-1349.

• Articles • Previous Articles     Next Articles

Empirical Likelihood Confidence Regions of the Parameters in Nonlinear Semiparametric Regression Models

  

  1. College of Mathematics and Science, Luoyang Normal University, |Henan Luoyang 471022;College of Applied Sciences, Beijing University of Technology, Beijing 100022
  • Received:2007-10-09 Revised:2008-12-30 Online:2009-10-25 Published:2009-10-25
  • Supported by:

    国家自然科学基金(10571008)、中国博士后科学基金(20080430633)和河南省自然科学研究项目(2008B110009)资助

Abstract:

In this paper, we consider the nonlinear semiparametric regression model, and construct the empirical log-likelihood ratio statistic for the unknown parameter. It is shown that the proposed statistics have the asymptotic standard chi-square distribution, and hence it can be used to construct the confidence region of the parameter. In addition, the least squares estimator of unknown parameter is constructed, and its asymptotic behavior is proved. A simulation study is carried out to compare the proposed methods with the least-squares method in terms of the confidence regions and its coverage probabilities.

Key words: Nonlinear semiparametric regression model,  Empirical likelihood, Chi-square distribution, Confidence region

CLC Number: 

  • 62G05
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