J4 ›› 2011, Vol. 46 ›› Issue (1): 92-96.
• Articles •
WANG Xiu-li1, 2, GAI Yu-jie2, LIN Lu2
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 chisquare 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.
linear model; estimating function; empirical likelihood; confidence region
WANG Xiu-li1, 2, GAI Yu-jie2, LIN Lu2. Empirical likelihood inference for the parameter in linear model with missing covariates[J].J4, 2011, 46(1): 92-96.
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