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  報告題目：Identify The Source of The Spikes: Factor or Mixture

主講人：潘光明教授（新加坡南洋理工大學）

時間：2025年12月17日（周三）10:00 a.m.

地點：北院卓遠樓305會議室

主辦單位：統計與數學學院

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.

主講人簡介：

潘光明，新加坡南洋理工大學教授，博士生導師。2005年博士畢業(yè)于中國科學技術大學；曾在新加坡國立大學、臺灣國立中山大學、荷蘭埃因霍溫科技大學做博士后和學術交流工作；2008年至今，在新加坡南洋理工大學工作；2013年遴選為國際統計學會會員（Elected Member of International Statistical Institute）；目前擔任《Random Matrices: Theory and Applications》期刊編委。研究領域包括計量經濟、高維統計推斷、隨機矩陣、多元統計等。主持新加坡國家基金項目5項，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等頂級雜志上發(fā)表60余篇學術論文。