报告题目：Some recent progress on nonlinear spatiotemporal modeling with application to housing price analysis
报告人：卢祖帝（Zudi Lu，南安普顿大学 教授/博导）
主持人：丁元耀 （数量经济研究所，教授）
时 间：2016年12月29日（周四）下午15:00-
地 点：加拿大28开奖网
412会议室
欢迎有兴趣的师生参加！
卢祖帝教授简介：
卢祖帝教授现为英国南安普顿大学统计科学研究所（s3ri）和数学科学学院统计学讲座教授，国际统计学会当选会员，澳大利亚国家研究基金会2010年度杰出青年基金获得者。研究方向包括：非线性金融时间序列模型和金融统计、非线性时空模型的统计推断和计算、非参数/半参数模型统计推断、统计学习、医学统计、贝叶斯统计等。担任顶级杂志Journal of Time Series Analysis的副主编和Cogent Mathematics杂志统计部分的主编。在统计学年鉴，英国皇家统计学会杂志, 经济理论,伯努利等世界顶级学术期刊发表论文50余篇。
内容提要：
Larger amounts of spatial or spatiotemporal data with more complex structures collected at irregularly spaced sampling locations are prevalent in a wide range of disciplines. With few exceptions, however, practical econometric and statistical methods for nonlinear 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 nonparametric methods for probability, including joint, density estimation, and semiparametric
models for a class of spatio-temporal nonlinear regression permitting possibly nonlinear relationship between response and covariates, with location-dependent spatial neighbouring and temporal lag effects taken account of. In the setting of semiparametric spatiotemporal modelling, a computationally feasible data-driven method is also shown for spatial weight matrix estimation. For illustration, our methodology is applied to investigate some land and housing prices data sets.
