BAYESIAN PREDICTION IN LINEAR-MODELS - APPLICATIONS TO SMALL AREA ESTIMATION

• 成果类型: Article
• 署名作者: DATTA, GS; GHOSH, M
• 署名单位: State University System of Florida; University of Florida; United States Department of Labor
• 刊物名称: ANNALS OF STATISTICS
• ISSN/ISSBN: 0090-5364
• DOI: 10.1214/aos/1176348369
• 发表日期: 1991
• 页码: 1748-1770
• 关键词: error; distributions

摘要

This paper introduces a hierarchical Bayes (HB) approach for prediction in general mixed linear models. The results find application in small area estimation. Our model unifies and extend, a number of models previously considered in this area. Computational formulas for obtaining the Bayes predictors and their standard errors are given in the general case. The methods are applied to two actual data sets. Also, in a special case, the HB predictors are shown to possess some interesting frequentist properties.