标题： 参数变换 Fay-Herriot 模型用于小区域估计 显示英文标题

标题： Parametric Transformed Fay-Herriot Model for Small Area Estimation

摘要： 在本文中，我们考虑参数变换的Fay-Herriot模型，并明确在何种变换条件下变换的估计量是一致的。结果显示，双次幂变换满足这些条件。基于参数估计量的渐近性质，我们推导了经验最佳线性无偏预测值（EBLUP）的预测误差的二阶近似，并得到了预测误差的二阶无偏估计量。最后，通过模拟和实证研究考察了所提出方法的性能。 显示英文摘要

摘要： In this paper, we consider parametric transformed Fay-Herriot models, and clarify conditions on transformations under which the estimator of the transformation is consistent. It is shown that the dual power transformation satisfies the conditions. Based on asymptotic properties for estimators of parameters, we derive a second-order approximation of the prediction error of the empirical best linear unbiased predictors (EBLUP) and obtain a second-order unbiased estimator of the prediction error. Finally, performances of the proposed procedures are investigated through simulation and empirical studies.