Representative Points of Statistical Distributions - Ye, Huajun; Fang, Kai-Tai; Zhou, Yongdao
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Statistical simulation has become a cornerstone in both statistical research and applications, particularly through the Monte Carlo (MC) method. One of the pioneering resampling techniques is the bootstrap method. This book explores the use of simulation to construct approximate distributions via representative points.

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Produktbeschreibung
Statistical simulation has become a cornerstone in both statistical research and applications, particularly through the Monte Carlo (MC) method. One of the pioneering resampling techniques is the bootstrap method. This book explores the use of simulation to construct approximate distributions via representative points.
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Autorenporträt
Kai-Tai Fang is a reputable statistician. He was educated at Peking University and The Chinese Academy of Sciences for undergraduate and postgraduate studies. He was elected as a Fellow by the Institute of Mathematical Statistics (IMS) in 1992 and a Fellow by the American Statistical Association (ASA) in 2001 as well as an elective member of the International Statistical Institute (ISI) in 1985. Professor Fang visited Yale University and Stanford University for two years and was invited as a Guest Professor at the Swiss Federal Institute of Technology and a Visiting Professor at the University of North Carolina at Chapel Hill. He was Chair Professor of the Department of Mathematics at Hong Kong Baptist University from 1993 to January 2006. Now, he is a Chair Professor at BNUHKBU United International College. His research interests are in statistics and mathematics, specifically experimental design, multivariate analysis, and data mining. He published 24 books (including six monographs in English) and more than 300 referred papers. Huajun Ye received a Bachelor and a Master's degrees in Probability and Mathematical Statistics from Peking University in 1999 and 2002, respectively. He received a PhD in Statistics from Manchester University, U.K. 2005, and his PhD research on covariance structures modeling of longitudinal data. In 2007, He joined BNU-HKBU United International College as an Assistant Professor. Now, he is a full Professor in the Department of Statistics and Data Science at BNU-HKBU United International College. His research interests include statistical modeling, inference, financial risk management, and statistical representative points. More than ten research papers have been published in international journals and conferences, including Biometrika, Mathematics, Journal of Complexity, Journal of Statistical Computation and Simulation, etc. Yongdao Zhou received a B.S. degree in pure mathematics in 2002 and M.S. and Ph.D. in Statistics in 2005 and 2008, respectively, from Sichuan University, China. He was a postdoctoral fellow at HKBU-UIC Joint Institute of Research Studies. Then, he joined Sichuan University and was a full professor after 2015. In 2017, he joined Nankai University, where he is presently a full professor in statistics. He visited UCLA, the University of Manchester, the National University of Singapore, and Simon Fraser University as a visiting scholar. His research agenda focuses on experimental design and big data analysis. He published over 70 papers, such as in JRSSB, JASA, Biometrika, and IEEE TKDE, as well as eight monographs and textbooks. His research publications have won two best paper awards.