Academic Report of the School of Mathematical Sciences [2025] No. 097  

(High-Level University Construction Series Report No. 1119)  

Lecture Title: Simultaneous Outlier Detection and Prediction for Kriging with True Identification  

Lecturer: Associate Professor Wang Zhanfeng (University of Science and Technology of China, USTC)  

Lecture Time: October 20, 2025, 16:00-17:00 (afternoon)  

Venue: Conference Room 514, Huixing Building, Yuehai Campus, Shenzhen University  

Abstract:  

Kriging with interpolation is widely used in various noise-free areas, such as computer experiments. However, owing to its Gaussian assumption, it is susceptible to outliers, which affects statistical inference, and the resulting conclusions could be misleading. Little work has explored outlier detection for kriging. Therefore, we propose a novel kriging method for simultaneous outlier detection and prediction by introducing a normal-gamma prior, which results in an unbounded penalty on the biases to distinguish outliers from normal data points. We develop a simple and efficient method, avoiding the expensive computation of the Markov chain Monte Carlo algorithm, to simultaneously detect outliers and make a prediction. We establish the true identification property for outlier detection and the consistency of the estimated hyperparameters in kriging under the increasing domain framework as if the number and locations of the outliers were known in advance. Under appropriate regularity conditions, we demonstrate information consistency for prediction in the presence of outliers.Numerical studies and real data examples show that the proposed method generally provides robust analyses in the presence of outliers.

Lecturer’s Biography:  

Wang Zhanfeng is an Associate Professor, Doctoral Supervisor, and Director of the Master's Program in Applied Statistics at the Department of Statistics and Finance, University of Science and Technology of China (USTC). He obtained his Bachelor's degree and Doctor of Science degree from USTC in 2003 and 2008, respectively. His main research focuses on biostatistics, functional data analysis, and non-Euclidean data analysis. He has published over 60 papers in academic journals including JASA, JBES, Biometrics, JCGS. He has led one National Natural Science Foundation of China (NSFC) Youth Program and two NSFC General Programs, and participated in two NSFC Key Programs. He currently serves as Chairman of the Tourism Big Data Branch of the Chinese Association of Applied Statistics.

Faculty and students are welcome to attend!  

Inviter: Zhou Yan  

School of Mathematical Sciences  

October 17, 2025