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学术报告

A method of constructing maximin distance designs

李文龙（博士后）

（北京理工大学）

报告时间： 2023年4月20日 (星期四) 下午3：00-4：00

报告地点：沙河国实二期E706

报告摘要：One attractive class of space-filling designs for computer experiments is that of maximin distance designs. Algorithmic search for such designs is commonly used but this method becomes ineffective for large problems. Theoretical construction of maximin distance designs is challenging; some results have been obtained recently, often by employing highly specialized techniques. This paper presents an easy-to-use method for constructing maximin distance designs. The method is versatile as it is applicable for any distance measure. Our basic idea is to construct large designs from small designs and the method is effective because the quality of large designs is guaranteed by that of small designs, as evaluated by the maximin distance criterion.

报告人简介：李文龙，现为北京理工大学数学与统计学院博士后，合作导师为田玉斌教授，研究方向为试验设计和计算机试验。2017年于南开大学获统计学博士学位，博士期间在加拿大西蒙弗雷泽大学联合培养1年，博士毕业论文被评为2022年南开大学优秀博士学位论文。现已在统计学期刊《中国科学》、《Biometrika》、《Journal of Statistical Planning and Inference》、《Statistical Papers》等期刊上发表多篇论文。目前正主持一项青年基金和一项博士后面上基金。

邀请人： 罗雪