報告題目：Paired or partially paired two-sample tests with unordered samples
報 告 人：葉志盛 副教授 新加坡國立大學
報告時間：2023年4月6日 10:00-11:00
報告地點：騰訊會議 會議 ID：363628179
校内聯系人：趙世舜 zhaoss@jlu.edu.cn
報告摘要：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.
報告人簡介：葉志盛副教授于2008年獲得清華大學材料科學與工程、經濟學雙學士學位，博士畢業于新加坡國立大學。現任新加坡國立大學工業系統工程與管理系副教授。葉教授的主要研究方向包括應用概率、統計相依模型、退化分析、可靠性建模以及随機管理等。在Technometrics，Journal of Quality Technology，Naval Research Logistics，IEEE Transactions on Reliability等國際知名期刊上發表高水平論文60餘篇。
