平特五不中

Title: Weighted empirical processes听

Empirical processes concern the uniform behavior of averaged sums over a sample of observations where the sums are indexed by a class of functions. Classical empirical processes typically study the empirical distribution function over the real line, while more modern empirical processes study much more general indexing function classes (e.g., Vapnik-Chervonenkis class, smoothness class); typical results include moment bounds and deviation inequalities. In this talk we will survey some of these results, but for the weighted empirical process that is obtained by weighing the original process by a factor related to the standard deviation of the process, which will make the resulting process more difficult to bound. Applications to multivaraite rank order statistics and residual empirical processes will be discussed.

Dr. Yue Zhao is an Assistant Professor in the Department of Mathematics at University of York, UK. He studied experimental cosmology (Ph.D. from Princeton in 2010) before switching to statistics (Ph.D. from Cornell in 2015). After postdoctoral studies at 平特五不中 (2015-16) and KU Leuven (2016-19), He joined York in 2019. His research mainly focuses on copula and high-dimensional statistics, and tools from empirical process theory and U-statistics/U-processes.

Meeting ID: 843 0865 5572

Passcode: 690084

听