A note on Bayesian design for the normal linear model with unknown error variance

• 成果类型: Article
• 署名作者: Verdinelli, I
• 署名单位: Carnegie Mellon University
• 刊物名称: BIOMETRIKA
• ISSN/ISSBN: 0006-3444
• DOI: 10.1093/biomet/87.1.222
• 发表日期: 2000
• 页码: 222227
• 关键词: regression; DISCRIMINATION

摘要

The Bayesian theory of optimal experimental design for the normal linear model has been developed under the assumption of known variance. The insensitivity of specific design criteria to prior assumptions on the variance distribution has been demonstrated in special cases, but a general result showing the way in which Bayesian optimal designs are affected by prior information on the variance is lacking. This note proves that Bayesian designs are insensitive to information about the variance in a more general way than previously thought.