Deviance information criterion for Bayesian model selection: Justification and variation

• المؤلفون الرئيسيون: LI, Yong, Jun YU, ZENG, Tao
• التنسيق: text
• اللغة: English
• منشور في: Institutional Knowledge at Singapore Management University 2017
• الموضوعات: AIC; DIC; Bayesian Predictive Distribution; Plug-in Predictive Distribution; Loss Function; Bayesian Model Comparison; Frequentist Risk; Econometrics
• الوصول للمادة أونلاين: https://ink.library.smu.edu.sg/soe_research/1927; https://ink.library.smu.edu.sg/context/soe_research/article/2926/viewcontent/DICTheory10.pdf
• المؤسسة: Singapore Management University

Deviance information criterion (DIC) has been extensively used for making Bayesian model selection. It is a Bayesian version of AIC and chooses a model that gives the smallest expected Kullback-Leibler divergence between the data generating process (DGP) and a predictive distribution asymptotically....