J4 ›› 2011, Vol. 46 ›› Issue (1): 92-96.

• Articles • Previous Articles     Next Articles

Empirical likelihood inference for the parameter in linear model with missing covariates

WANG Xiu-li1, 2, GAI Yu-jie2,  LIN Lu2   

  1. 1. School of Mathematical Science, Shandong Normal University, Jinan  250014, Shandong, China;
    2. School of Mathematical Science, Shandong University, Jinan 250100, Shandong,  China
  • Received:2010-04-29 Online:2011-12-14 Published:2011-03-16

Abstract:

The empirical likelihood inference for the parameter of interest in linear model with missing covariates is considered. Using the inverse probability-weighted method, the estimating function for the unknown parameter is constructed. The empirical log-likelihood ratio based on our estimating function is proved, under some suitable conditions, to be a standard chisquare distribution asymptotically. With this result,  the confidence region for the parameter can be constructed. At last,  our result is further verified through some numerical simulations.

Key words:  linear model; estimating function; empirical likelihood; confidence region

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