题目：Semiparametric spatial time series modelling and data-driven spatial weight matrix  estimation: A personal review

　　报告人： Zudi Lu  (University of Southampton, UK)

　　Abstract: K Larger amounts of time-series data with more complex structures collected at irregularly spaced sampling locations are becoming more prevalent in a wide range of disciplines. With few exceptions, however, practical statistical methods for modeling and analysis of such data remain elusive. In this talk, I provide a review on some developments and progress of the research that my co-authors and I have recently done. In particular, we will look at some semiparametric models, such as a class of spatio-temporal autoregressive partially nonlinear regression models, which permits possibly nonlinear relationships between responses and covariates. In addition, the dependence structure is stationary over time but nonstationary over space, while the sampling grids can be irregular. We develop a computationally feasible data-driven method for spatial weight matrix estimation in semiparametric spatial time series modelling. For illustration, our methodology is applied to investigate housing prices in relation to consumer price index in the United States.

　　时间：2015年7月15日（周三）16:00-17:00

　　地点：首都师大北一区文科楼 707 教室

　　欢迎全体师生积极参加！