Recording: https://disk.pku.edu.cn:443/link/C0611FF18351179DC19875AD9B489896
Valid Until: 2027-06-30 23:59
Abstract: The classical proof of the central limit theorem is based on the characteristic function or the Fourier transform. It works well for sums of independent random variables. The Stein method is a completely novel approach that works not only for independent random variables but also for dependent random variables. It works for both normal and non-normal approximation. It can also provide the accuracy of approximation. In this talk, we will give a brief review on the fundamentals of Stein's method and recent developments in this area.
Bio: Qi-Man Shao, Chair Professor at Southern University of Science and Technology, China. His main research areas are the limit theory in probability and the asymptotic large sample theory in statistics. He has made fundamental contributions to the self-normalized limit theory and the Stein method for normal and non-normal approximation. Noticeable honors and professional services include: an invited speaker at the ICM 2010 in Hyderabad; IMS Medallion Lecturer, a Keynote Speaker at the 2011 Joint Statistical Meetings; State National Science Award (2nd class) (2015); co-Editor, The Annals of Applied Probability (1/2022 - 12/2024); Associate Editor, Bernoulli (1/2013 - 12/2021); Associate Editor, The Annals of Statistics (11/2003 - 12/2012).
