论文标题
小面积估计的具有高维参数的嵌套误差回归模型
A Nested Error Regression Model with High Dimensional Parameter for Small Area Estimation
论文作者
论文摘要
在本文中，我们提出了一个具有高维参数的柔性嵌套误差回归小区域模型，该模型在回归系数和方差成分中融合了异质性。我们开发了一种新的健壮面积特异性估计方程方法，该方法允许在估计小区域特定模型参数时适当汇集大量区域。我们提出了一种参数引导程序和折刀方法，不仅估算了均方误差，还估算了其他常用的不确定性度量，例如标准误差和变异系数。我们进行基于模型和基于设计的模拟实验和现实数据分析以评估所提出的方法论
In this paper we propose a flexible nested error regression small area model with high dimensional parameter that incorporates heterogeneity in regression coefficients and variance components. We develop a new robust small area specific estimating equations method that allows appropriate pooling of a large number of areas in estimating small area specific model parameters. We propose a parametric bootstrap and jackknife method to estimate not only the mean squared errors but also other commonly used uncertainty measures such as standard errors and coefficients of variation. We conduct both modelbased and design-based simulation experiments and real-life data analysis to evaluate the proposed methodology
