时 间：2023年6月19日（周一）10：00-11：00
地 点: 理科大楼a1514室
题 目：adaptive order-of-addition experiments via the quick-sort algorithm
报告人：陈建斌 北京理工大学副研究员
主持人：王亚平 研究员
主 办：统计学院
摘 要：
the order-of-addition (oofa) experiment has received a great deal of attention in the recent literature. the primary goal of the oofa experiment is to identify the optimal order in a sequence of m components. all the existing methods are model-dependent and are limited to small number of components. the appropriateness of the resulting optimal order heavily depends on (a) the correctness of the underlying assumed model, and (b) the goodness of model fitting. moreover, these methods are not applicable to deal with large m (e.g., m≥7). with this in mind, this article proposes an efficient adaptive methodology, building upon the quick-sort algorithm, to explore the optimal order without any model specification. compared to the existing work, the run sizes of the proposed method needed to achieve the optimal order are much smaller. theoretical supports are given to illustrate the effectiveness of the proposed method. the proposed method is able to obtain the optimal order for large m (e.g., m≥20). numerical experiments are used to demonstrate the effectiveness of the proposed method.
报告人简介：
北京理工大学副研究员，普渡大学博士后，2020年南开大学获得统计系博士学位，2009年，2016年分别在兰州大学获得本硕学位。曾先后访问宾州州立大学、佐治亚大学。研究兴趣包括试验设计、添加次序试验、计算机试验等。在european journal of operational research、technometrics、statistica sinica、information sciences、computers & industrial engineering等统计学国内外权威期刊发表论文10余篇。