时 间： 2020年7月 9日下午 14:00-17:00 (I)
2020年7月10日下午 14:00-17:00 (II)
2020年7月11日下午 14:00-17:00 (III)
报告人：宋心远 教授
主持人：唐炎林、於州、方方
摘 要：
This short course covers recent developments inBayesian modeling and data analysis. The course includes three sections.Section 1 introduces principles of Bayesian inference, including Bayesianupdating, prior specification, posterior derivation, data augmentation, MCMCalgorithm, and sensitivity analysis. Apart from estimation, Bayesianmodel/variable selection methods, such as Bayes factor, deviance informationcriterion, and Bayesian Lasso, are described. Section 2 introduces Bayesianmodels for discrete, semicontinuous/zero-inflated, longitudinal, heterogeneous,and missing data. Section 3 discusses Bayesian approach for joint modeling ofmultiple data types. Real applications are used to illustrate themethodologies.
个人简介：
Xinyuan Song is a full professor andChair of the Department of Statistics, Chinese University of Hong Kong. Herresearch interests are latent variable models, nonparametric and semiparametricmodeling, Bayesian methods, statistical computing, and survival analysis. Sheserves/served as an associate editor for a number of international journals inStatistics and Psychometrics, including Psychometrika, Structural EquationModeling, Biometrics, Canadian Journal of Statistics, and ComputationalStatistics and Data Analysis. She has published over 140 papers ininternational journals in statistics, biostatistics, psychometrics, and otherinterdisciplinary areas.