Regression modelSurvey estimation
Fay-Herriot模型（小区域估计）
小区域估计（Small Area Estimation, SAE）是指那些能够为亚群体（如地理区域、人口群体或行政单位）提供可靠估计的统计技术，这些亚群体的直接抽样样本量太少，无法达到可接受的精度。Fay-Herriot模型由Robert Fay和Roger Herriot于1979年提出，是经典的区域层面SAE模型。它通过经验贝叶斯（empirical Bayes）或最佳线性无偏预测（BLUP）框架，补充了薄弱的直接抽样估计，并利用辅助协变量信息，显著降低了小域的均方误差。
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来源
- Fay, R. E., & Herriot, R. A. (1979). Estimates of income for small places: An application of James-Stein procedures to census data. Journal of the American Statistical Association, 74(366), 269–277. DOI: 10.1080/01621459.1979.10482505 ↗
如何引用本页
ScholarGate. (2026, June 2). Small Area Estimation (Fay-Herriot Model). ScholarGate. https://scholargate.app/zh/survey-methodology/small-area-estimation
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