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  报告题目：Identify The Source of The Spikes: Factor or Mixture

主讲人：潘光明教授（新加坡南洋理工大学）

时间：2025年12月17日（周三）10:00 a.m.

地点：北院卓远楼305会议室

主办单位：统计与数学学院

摘要：

This talk is about identifying the sources of spiked sample eigenvalues. We consider the problem of identifying the pattern of latent variables in high-dimensional linear latent variable models, which can also be interpreted as determining the source of spiked singular values in the data matrix. Specifically, we test whether the latent variables are continuous or categorical, a distinction which is crucial for data interpretation but challenging when the dimensionality is comparable to the sample size. To address this inference problem, we analyze the asymptotic behavior of empirical measures associated with singular vectors corresponding to large spiked singular values. Leveraging these insights, we propose a novel test statistic based on the eigenvector quantile differences and establish its theoretical performance under the null hypothesis. Simulation studies and real data analyses for breast cancer and glioblastoma gene expression datasets demonstrate the effectiveness and practical utility of our method.

主讲人简介：

潘光明，新加坡南洋理工大学教授，博士生导师。2005年博士毕业于中国科学技术大学；曾在新加坡国立大学、台湾国立中山大学、荷兰埃因霍温科技大学做博士后和学术交流工作；2008年至今，在新加坡南洋理工大学工作；2013年遴选为国际统计学会会员（Elected Member of International Statistical Institute）；目前担任《Random Matrices: Theory and Applications》期刊编委。研究领域包括计量经济、高维统计推断、随机矩阵、多元统计等。主持新加坡国家基金项目5项，已在Journal of the Royal Statistical Society Series B 、Annals of Statistics、Journal of American the Statistical Association、Annals of Probability、Annals of Applied Probability、Bernoulli、IEEE Transactions on Signal Processing、IEEE Transactions on Information Theory等顶级杂志上发表60余篇学术论文。