Mathematical Sciences: Bayesian Experimental Design and Prior Elicitation in Response to Surface Models

点击翻译按钮获取中文摘要

This project begins the preliminary research in the development and implementation of optimal Bayesian experimental designs based on expert opinion and informative priors. Expansions from fixed designs derived from fractional factorial designs will include sequential designs for response surfaces and designs for yield optimization. The role and practicalities of prior elicitation processes will also be examined. Bayesian statistical methodology allows direct incorporation of expert opinion or of good prior information, as is often available for experiments in physical science and manufacturing. This project will develop Bayesian optimal designs for experiments for response surface models, for yield optimization and for particular application with the Taguchi method.