多重响应的非参数预测的渐近贝叶斯设计(英文)

Asymptotic Bayesian Design Nonparametric Multiresponse Prediction

本文研究在单位方体上多重响应预测的试验设计问题.将多重响应函数视作相互独立的无限维随机过程的实现,因此我们采用非参数贝叶斯方法及渐近技术建立渐近贝叶斯设计准则.在一定条件下,我们证明单位方体上的均匀设计测度是最优渐近贝叶斯设计.

This paper deals with Bayesian design in the unit cube for multiresponse prediction with infinite-dimensional random functions as priors. In order to make optimization more tractable, we adopt the asymptotics used in Mitchell et al. (1994). It is shown that the uniform continuous design on the unit cube is optimum under the asymptotic Bayes criterion for a certain prior specification. It follows that the uniform design proposed by Fang and Wang (1994) performs very well for the multiresponse prediction.