The construction of confidence intervals for quantiles of a population under a associated sample is studied by using the blockwise technique. It is shown that the blockwise empirical likelihood (EL) ratio statistic ...The construction of confidence intervals for quantiles of a population under a associated sample is studied by using the blockwise technique. It is shown that the blockwise empirical likelihood (EL) ratio statistic is asymptotically X2-type distributed, which is used to obtain EL-based confidence intervals for quantiles of a population.展开更多
Oonsider two linear models Xi = U'β + ei, Yj = V1/2y + ηj with response variables missing at random. In this paper, we assume that X, Y are missing at random (MAR) and use the inverse probability weighted imput...Oonsider two linear models Xi = U'β + ei, Yj = V1/2y + ηj with response variables missing at random. In this paper, we assume that X, Y are missing at random (MAR) and use the inverse probability weighted imputation to produce 'complete' data sets for X and Y. Based on these data sets, we construct an empirical likelihood (EL) statistic for the difference of X and Y (denoted as A), and show that the EL statistic has the limiting distribution of X~, which is used to construct a confidence interval for A. Results of a simulation study on the finite sample performance of EL-based confidence intervals on A are reported.展开更多
基金Supported by the National Natural Science Foundation of China(No.11271088,11201088,11361011)the Natural Science Foundation of Guangxi(N0.2013GXNSFAA019004,2013GXNSFAA019007,2013GXNSFBA019001)+1 种基金the New Century Ten,Hundred and Thousand Talents Project of Guangxithe Youth Foundation of Guangxi Normal University
文摘The construction of confidence intervals for quantiles of a population under a associated sample is studied by using the blockwise technique. It is shown that the blockwise empirical likelihood (EL) ratio statistic is asymptotically X2-type distributed, which is used to obtain EL-based confidence intervals for quantiles of a population.
基金Supported by the National Natural Science Foundation of China(No.11271088,11361011,11201088)Natural Science Foundation of Guangxi(No.2013GXNSFAA(019004 and 019007),2013GXNSFBA019001)
文摘Oonsider two linear models Xi = U'β + ei, Yj = V1/2y + ηj with response variables missing at random. In this paper, we assume that X, Y are missing at random (MAR) and use the inverse probability weighted imputation to produce 'complete' data sets for X and Y. Based on these data sets, we construct an empirical likelihood (EL) statistic for the difference of X and Y (denoted as A), and show that the EL statistic has the limiting distribution of X~, which is used to construct a confidence interval for A. Results of a simulation study on the finite sample performance of EL-based confidence intervals on A are reported.