报告时间：12月15日下午14:00-17:00

报告地点：统计学院213报告厅

报告（一）

报告题目：A note on constructing clear compromise plans

报告人：周琦 副教授

报告摘要：The regular two-level fractional factorial designs of n factors and N runs, having resolution IV and allowing experimenters to clearly estimate all main effects and a set of required two-factor interactions (2fi’s), are called clear compromise plans. Four classes of clear compromise plans have been discussed in the literature. The general minimum lower order confounding (GMC) is an elaborate criterion, which was proposed to select optimal fractional factorial designs. This paper gives a theory on constructing a set of class three clear compromise plans with 5N/32+ 3 ≤ n ≤ N/4+ 1, called partially general minimum lower order confounding (P-GMC) designs. We first prove that each P-GMC design is constructed by a GMC design and two specified columns. Then we study the properties of these designs. For N = 32, 64 and 128, we illustrate that the P-GMC designs are admissible designs. Furthermore, they all have GMC, except for the P-GMC 2¹³⁻⁷ and 2²³⁻¹⁶ designs.

报告时间：12月15日14:00-15:00

报告人简介：周琦：2013年毕业于东北师范大学获理学博士学位，主要研究先验信息下因子试验的设计与分析。至今已发表SCI论文9篇，主持国家自然金数学天元项目、青年、面上项目各一项，参与国家级项目8项。现为国家自然基金数理学部函评专家、Mathematical Reviews特约评论员、4种SCI期刊匿名审稿人、天津市131人才工程第2层次入选者、中国现场统计研究会试验设计分会理事。

报告（二）

报告题目：Uniform projection nested Latin hypercube designs

报告人：陈浩 博士

报告摘要：Computer experiments usually involve many factors, but only a few of them are active. In such a case, it is desirable to construct designs which have good projection properties. Maximum projection designs and uniform projection designs have been developed for common experimental situations, however, there has been little study on constructing projection designs for high-accuracy computer experiments (HEs) and low-accuracy computer experiments (LEs) so far. In this paper, we propose a weighted uniform projection criterion, and construct uniform projection nested Latin hepercube designs to suit such computer experiment situations. We show that the obtained designs have good projection properties in all sub-dimensions, and we also discuss how to choose a proper value for the weight. Simulated examples are available to illustrate the effectiveness of the proposed designs.

报告时间：12月15日15:00-16:00

报告人简介：陈浩：天津财经大学硕士生导师。天津市现场统计研究会常务理事、副秘书长，中国现场统计研究会试验设计分会理事。研究方向：计算机试验设计与数据分析、最优试验设计。2013年12月于南开大学获理学博士学位，2018年4月-2019年4月访问佛罗里达大学生物统计系。发表SCI论文7篇，主持国家自然科学基金2项，入学天津市“131”创新型人才培养工程第二层次，获第三次全国农业普查研究课题评审三等奖。

报告（三）

报告题目：Column-orthogonal designs with multi-dimensional stratification

报告人：杨雪 博士

报告摘要：Orthogonal Latin hypercube design and its relaxation, column-orthogonal design, are two kinds of orthogonal designs for computer experiments. However, they usually do not achieve maximum stratification in multi-dimensional margins. In this paper, we propose some methods to construct column-orthogonal designs with multi-dimensional stratification by rotating symmetric and asymmetric orthogonal arrays. The newly constructed column-orthogonal designs ensure that the estimates of all linear effects are uncorrelated with each other and even uncorrelated with the estimate of all second-order effects (quadratic effects and bilinear effects) when the rotated orthogonal arrays have strength larger than two. Besides orthogonality, the resulting designs also preserve better space-filling property than those constructed by using the existing methods. In addition, we provide a method to construct a new class of orthogonal Latin hypercube designs with multi-dimensional stratification by rotating regular factorial designs. Some newly constructed orthogonal Latin hypercube designs are tabulated for practical use.

报告时间：12月15日16:00-17:00

报告人简介：杨雪：2015年于南开大学获得理学博士学位并入职天津财经大学；2016.12-至今在南开大学统计与数据科学学院从事博士后研究工作；入选天津“131”人才工程第三层次；天津市现场统计研究会理事。第一作者在 “Statistica Sinica” 和 “Statistics and Probability Letter”等国际统计学期刊发表SCI检索论文5篇，第二作者发表教改论文1篇。主持在研国家自然科学基金青年基金项目1项，主持在研中国博士后基金面上项目1项。参与完成国家自然科学基金数学天元基金项目1项，参与在研国家级项目4项，省部级项目3项，天津市社会科学基金项目1项。