报告题目：Paired or partially paired two-sample tests with unordered samples

报 告 人：叶志盛 副教授 新加坡国立大学

报告时间：2023年4月6日 10:00-11:00

报告地点：腾讯会议 会议 ID：363628179

校内联系人：赵世舜 zhaoss@jlu.edu.cn

报告摘要：In paired two-sample tests for mean equality, it is common to encounter unordered samples in which subject identities are not observed or unobservable, and it is impossible to link the measurements before and after treatment. The absence of subject identities masks the correspondence between the two samples, rendering existing methods inapplicable. In this talk, we introduce two novel testing approaches. The first splits one of the two unordered samples into blocks and approximates the population mean using the average of the other sample. The second method is a variant of the first, in which subsampling is used to construct an incomplete U-statistic. Both methods are affine invariant and can readily be extended to partially paired two-sample tests with unordered samples. Asymptotic null distributions of the proposed test statistics are derived and the local powers of the tests are studied. Comprehensive simulations show that the proposed testing methods are able to maintain the correct size, and their powers are comparable to those of the oracle tests with perfect pair information. Four real examples (including a phone degradation test) are used to illustrate the proposed methods, in which we demonstrate that naive methods can yield misleading conclusions.

报告人简介：叶志盛副教授于2008年获得清华大学材料科学与工程、经济学双学士学位，博士毕业于新加坡国立大学。现任新加坡国立大学工业系统工程与管理系副教授。叶教授的主要研究方向包括应用概率、统计相依模型、退化分析、可靠性建模以及随机管理等。在Technometrics，Journal of Quality Technology，Naval Research Logistics，IEEE Transactions on Reliability等国际知名期刊上发表高水平论文60余篇。