报告学者：王春燕

报告者单位：中国人民大学

报告时间：2024年11月4日（周一）上午10:00-11:00

报告地点：7号楼 会议室7215

报告摘要：Two-level orthogonal arrays ensure the independent estimations of main effects when linear models are considered, and thus are popularly used experimental designs. Such arrays can be classified into regular and nonregular designs. Regular designs entertain specific algebraic structures and thus have been well-studied in the literature. Their run sizes, however, are limited to powers of 2. Nonregular designs have a more complicated structure, but they are more flexible in the run sizes and allow the estimation of more effects. The construction of nonregular designs remains a challenge. This paper introduces a new class of nonregular designs called isomorphic foldovers design (IFD). Specifically, it is composed of several foldovers of an initial design. The goal of our study is to investigate the general theory of IFDs. We propose a method for obtaining all nonequivalent IFDs with f foldovers for any initial design. Two algorithms are provided to construct optimal f-IFD in terms of G-aberration (or G_2-aberration) criterion. The IFD structure provides an efficient way to find good designs in the sense that constructing good IFDs based on a nonregular initial design is often more successful than doing so with a more granular single flat. Meanwhile, the IFDs have a parallel flats structure and thus are much easier to understand and analyze than many other nonregular designs. Moreover, we show that some existing designs can be viewed as special cases of IFDs.

报告学者简介：王春燕，南开大学博士，普渡大学博士后助理研究员，现为中国人民大学统计学院副教授，研究方向包括统计试验设计、计算机试验、次序添加试验等。相关论文发表在《中国科学：数学》、《Annals of Statistics》、《Statistica Sinica》上。