"Asymptotic Correction of Empirical Bayes Confidence Intervals and its Application to Small Area Estimation" (in Japanese)
"Asymptotic Correction of Empirical Bayes Confidence Intervals and its Application to Small Area Estimation" (in Japanese)
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“经验贝叶斯置信区间的渐近修正及其在小区域估计中的应用”（日语）
DOI：
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发表时间：
2005
期刊：
影响因子：
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通讯作者：
T. Kubokawa
中科院分区：
文献类型：
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作者：
Yoshitaka Sasase;T. Kubokawa
本文讨论了随机效应或混合效应线性模型中小面积均值置信区间的构造问题。基于经验贝叶斯方法的粗置信区间的缺点是其覆盖概率远小于名义置信系数。为了改进该置信区间，本文给出了调整临界值的步骤，当小区域个数较多时，得到的置信区间具有与名义置信系数二阶渐近一致的覆盖概率。建议的置信区间数值模拟实验的基础上进行研究，并应用于公布的地价数据。这些数值研究说明了该建议的实际效用。
This paper addresses the issue of constructing a confidence interval of a small area mean in a random effect or mixed effects linear model. A crude confidence interval based on the empirical Bayes method has the drawback that its coverage probability is much less than a nominal confidence coefficient. For improving on this confidence interval, the paper provides the procedure of adjusting the critical value, and the resulting confidence interval has a coverage probability which is identical to the nominal confidence coefficient in second order asymptotics when the number of small areas is large. The proposed confidence interval is numerically investigated based on simulation experiments and applied to posted land price data. These numerical studies illustrate the practical usefulness of the proposal.