Shenzhen University School of Mathematical Sciences  

Liyuan Scholars Colloquium Session 152  

Lecture Title: Structure Identification in Clustered Data Analysis  

Speaker: Chair Professor Zhang Wenyang (University of Macau)  

Time: 14:00-15:00, November 21, 2025 (Friday)  

Location: Classroom 1, Huixing Building, Yuehai Campus, Shenzhen University  

Abstract:  

Clustered data analysis is an important topic in data science. A well-established approach is to assume all clusters share the same unknown parameters of interest, and the difference between different clusters is formulated and accounted for by cluster effects. Whilst this approach works very well in many issues, such as exploring the global impact of an explanatory variable on the response variable, it does not provide much insight about individual attributes of each cluster. Assuming different clusters have completely different parameters would result in too many unknown parameters, which would lead to large variances of the final estimators. Following the idea of homogeneity pursuit, various modelling approaches are proposed in recent literature to group the unknown parameters and explore the individual attributes in clustered data analysis. However, most of them are either difficult to implement or require each cluster to have reasonably big cluster size. In this talk, I will present a new approach, which is easy to implement and does not require any cluster to have big size. I will also show its asymptotic properties without assuming the size of any cluster tends to infinity. I will also use intensive simulation studies to show the approach works very well when sample size is finite. Finally, I apply the approach to a well known financial dataset to show its superiority in exploring individual attributes in clustered data analysis.

Speaker Profile:  

Zhang Wenyang is a Chair Professor of Business Intelligence and Analytics at the University of Macau. He serves as an Associate Editor for two of the top three international statistics journals, Journal of the American Statistical Association and Annals of Statistics, and for the leading international journal in business and economic statistics, Journal of Business & Economic Statistics. His research focuses on big data analytics, financial data analysis, high-dimensional data analysis, nonparametric modeling, time series analysis, spatial data analysis, multilevel modeling, survival analysis, and structural equation modeling. He has published numerous influential papers in top international academic journals, with one of his papers on the ABC method cited over 3,600 times. He has previously taught at the London School of Economics and Political Science (UK), University of Kent (UK), University of Bath (UK), and University of York (UK). He served as a member of the Research Committee of the Royal Statistical Society (the third Chinese scholar in history to hold this position) and was an assessment panel member for the Hong Kong Special Administrative Region Government's six-yearly Research Assessment Exercise in 2020 and 2026.

All faculty and students are welcome!  

School of Mathematical Sciences  

November 17, 2025