Convergence properties of sequential Bayesian D

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• 作者：Anindya Roy ; Subhashis Ghosal ; William F. Rosenberger
• 关键词：Adaptive designs ; Asymptotic normality ; Discrete optimal design ; Dose– ; response ; Posterior convergence
• 刊名：Journal of Statistical Planning and Inference
• 出版年：2009
• 出版时间：1 February 2009
• 年：2009
• 卷：139
• 期：2
• 页码：425-440
• 全文大小：274 K

文摘

We establish convergence properties of sequential Bayesian optimal designs. In particular, for sequential D-optimality under a general nonlinear location-scale model for binary experiments, we establish posterior consistency, consistency of the design measure, and the asymptotic normality of posterior following the design. We illustrate our results in the context of a particular application in the design of phase I clinical trials, namely a sequential design of Haines et al. [2003. Bayesian optimal designs for phase I clinical trials. Biometrics 59, 591–600] that incorporates an ethical constraint on overdosing.