A Kullback-Leibler Divergence for Bayesian Model Diagnostics

• 作者: Chen-Pin Wang Malay Ghosh
• 来源期刊: 统计学期刊(英文)
• 学科: 医学
• 关键词: Kullback-Leibler Distance Model DIAGNOSTIC WEIGHTED POSTERIOR PREDICTIVE P-VALUE
• 年，卷（期）: 2011,（3）
• 页码范围: 172-184
• 页数: 13页
• 分类号: R73

摘要

This paper considers a Kullback-Leibler distance (KLD) which is asymptotically equivalent to the KLD by Goutis and Robert [1] when the reference model (in comparison to a competing fitted model) is correctly specified and that certain regularity conditions hold true (ref. Akaike [2]). We derive the asymptotic property of this Goutis-Robert-Akaike KLD under certain regularity conditions. We also examine the impact of this asymptotic property when the regularity conditions are partially satisfied. Furthermore, the connection between the Goutis-Robert-Akaike KLD and a weighted posterior predictive p-value (WPPP) is established. Finally, both the Goutis-Robert-Akaike KLD and WPPP are applied to compare models using various simulated examples as well as two cohort studies of diabetes.