Abstract We consider longitudinal data and the problem of prediction of subpopulation (domain) characteristics that can be written as a linear combination of the variable of interest, including cases of small or zero sample sizes in the domain and time period of interest. We consider the empirical version of the predictor proposed by Royall (1976) showing that it is a generalization of the empirical version of the predictor presented by Henderson (1950). We propose a parametric bootstrap MSE estimator of the predictor. We prove its asymptotic unbiasedness and derive the order of its bias. Considerations are supported by Monte Carlo simulation analyses to compare its accuracy (not only the bias) with other MSE estimators, including jackknife and weighted jackknife MSE estimators that we adapt for the considered predictor.

中文翻译：

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小区域预测问题中使用参数Bootstrap进行精度估计

摘要我们考虑纵向数据和预测亚种群（域）特征的问题，这些问题可以写成目标变量的线性组合，包括目标域和时间段内样本量较小或为零的情况。我们考虑了Royall（1976）提出的预测变量的经验版本，表明它是Henderson（1950）提出的预测变量的经验版本的推广。我们提出了预测器的参数自举MSE估计器。我们证明其渐近无偏，并推导出其偏序。蒙特卡洛模拟分析支持各种考虑因素，以与其他MSE估算器（包括折刀和加权折刀MSE估算器）比较其准确性（不仅是偏差），我们适合考虑的预测器。