Acta mathematica scientia,Series A ›› 2011, Vol. 31 ›› Issue (2): 360-368.

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Empirical Likelihood Inferences for Covariate Adjusted Regression

 ZHAO Pei-Xin1,2, XUE Liu-Gen1   

  1. 1.College of Applied Sciences, Beijing University of Technology, Beijing 100124|2.Department of Mathematics, Hechi University, Guangxi Yizhou |546300
  • Received:2008-10-28 Revised:2009-09-06 Online:2011-04-25 Published:2011-04-25
  • Supported by:

    国家自然科学基金 (10871013)、北京市自然科学基金 (1102008)、高等学校博士学科点专项科研基金(20070005003)、广西自然科学基金(2010GXNSFB013051)和研究生科研启动基金 (2008QS-N014) 资助

Abstract:

In this paper, an empirical likelihood inference for the covariate adjusted regression is investigated. Based on the empirical likelihood method,
a corrected empirical likelihood ratio method is proposed and the Wilks' phenomenon is derived. Then, the confidence intervals for the regression coefficients are constructed. A simulation study and a real data application are undertaken to assess the finite sample performance of the proposed method.

Key words: Covariate adjusted regression, Empirical likelihood, Confidence intervals

CLC Number: 

  • 62G05
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