Empirical Likelihood Inference for a Partially Linear Errors-in-variables Model with Covariate Data Missing at Random
 
 
 
 
  
 
  
   ACTA MATHEMATICAE APPLICATAE SINICA-ENGLISH SERIES
   
 
  
  
 DOI: 
  
   10.1007/s10255-016-0586-5
   
 
 出版年: 
  
   JUN 2016
   
  
 
 
  摘要
 
 
 The authors study the empirical likelihood method for partially linear errors-in-variables model with covariate data missing at random. Empirical likelihood ratios for the regression coefficients and the baseline function are investigated, and the corresponding empirical log-likelihood ratios are proved to be asymptotically standard chi-squared, which can be used to construct confidence regions. The finite sample behavior of the proposed methods is evaluated by a simulation study which indicates that the proposed methods are comparable in terms of coverage probabilities and average length of confidence intervals. Finally, the Earthquake Magnitude dataset is used to illustrate our proposed method.