Speaker: Prof. Xingwei Tong(Beijing Normal University)
Time: 2025-04-07 16:00-17:00
Venue: Lecture Hall 601
Abstract：We consider a linear model with a change point according to the unknown random threshold of a covariate. We give the EM estimation of the regression and change point parameters. The existence of the random change point is detected by the supremum (SUP) test of score statistics. Theoretically, we establish the convergency and asymptotic distribution of the estimation, and show that the EM estimates converge in distribution to normal distribution. In addition, the numerical performance of the proposed approach is demonstrated through simulation studies. Finally, applying our methodology to household financial decisions, the average debt tolerance of Chinese households is estimated to be 1.1364 times the sum of total household income and financial assets. The effect of assets and income on consumption shows a rapid decline if the household exceeds the average debt tolerance.
Tong Xingwei is a professor and doctoral supervisor at Beijing Normal University, where he currently serves as the Chair of the Department of Mathematical Statistics, as well as the Director of the Key Laboratory of Educational Psychology and Data Science Technology & Application in Guangdong Provincial Higher Education Institutions. He earned his Ph.D. from the School of Mathematical Sciences at Peking University and completed postdoctoral research at the University of Missouri, Columbia, USA. With long-term expertise in cutting-edge research areas such as biostatistics, financial statistics, causal analysis, and robust statistics, he holds several prominent academic positions, including Executive Council Member of the Causal Inference Society of China, Vice President of the China Industrial Statistics Teaching and Research Association, Executive Council Member of the International Biometric Society (China Chapter), and Vice President of the Beijing Big Data Association. He has led key research projects, including one under the Ministry of Science and Technology’s Key R&D Program, a sub-project of a National Natural Science Foundation of China (NSFC) Key Program, and multiple NSFC General Program grants. He has published over 50 academic papers in top-tier journals such as Annals of Statistics, Biometrika, and Statistica Sinica.
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