Optimal and Robust Strategies for Cluster Sampling
将Royall关于最优与稳健抽样策略的结果推广到整群抽样，并给出特定超总体模型下有限总体总量最佳线性无偏预测的模型方差下界。
Abstract This article extends Royall's (1992) results on optimal and robust sampling strategies to cluster sampling. It also gives the lower bound on the model-based variances of best linear unbiased predictors of finite population totals under certain classes of superpopulation models. Key Words: Best linear unbiased predictorFinite population samplingLower boundSuperpopulation model