报告人：Decai Liang (Peking University)
时间：2019-03-14 12:00-13:30
地点：Room 1418, Sciecnes Building No. 1
各位数院老师和研究生同学：
研究生学术午餐会是在学院领导的大力支持下，由研究生会负责组织的系列学术交流活动。午餐会每次邀请一位同学作
为主讲人，面向全院各专业背景的研究生介绍自己科研方向的基本问题、概念和方法，并汇报近期的研究成果和进展，是研究生展示自我、促进交流的学术平台。
研究生会已经举办了三十七期活动，我们将于2019年3月15日周五举办第三十八期学术午餐会活动，欢迎感兴趣的老师和同学积极报名参加。
报告人简介：梁德才，tyc234cc 太阳成集团2015级博士研究生，师从姚方教授，研究方向为时空统计、函数型数据。曾在2017-2018学年访问美国迈阿密大学Yongtao Guan教授。
Abstract: Severe air pollution affects billions of people around the world, particularly in developing
countries such as China. Effective emission control policies rely primarily on proper assessment of air
pollutants and accurate spatial clustering outcomes. Unfortunately, emission patterns are difficult to
observe as they are highly confounded by many meteorological and geographical factors. The standard
clustering techniques generally fail to exploit the spatiotemporal features of data. We propose a novel
approach for modeling and clustering daily PM2.5 concentrations all over China. Observed concentrations
from monitoring stations are modeled as spatially dependent functional data. We assume the latent
emission processes originate from a functional mixture model with each component as a spatiotemporal
process. Cluster memberships of stations follow a Markov random field model and geographical factors
are also considered. The superior performance of our approach compared to others is demonstrated using
extensive simulation studies. Our method is effective in dividing China and also the Beijing-Tianjin-Hebei
region into several regions based on PM2.5 concentrations, suggesting separate local emission control policies are needed.
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