讲座编号:jz-yjsb-2022-y006
讲座问题:Spatial-temporal Model with Heterogeneous Random Effects
主 讲 人:冯兴东 教授 上海财经大学
讲座时间:2022年4月13日(星期三)下午14:00
讲座所在:腾讯聚会,聚会ID:851 813 567
加入工具:数学与统计学院全体西席及研究生
主理单位:数学与统计学院、研究生院
主讲人简介:
冯兴东,上海财经大学统计与治理学院院长、统计学教授、博士生导师。研究领域为数据降维、稳健要领、分位数回归以及在经济问题中的应用、大数据统计盘算、强化学习等,在国际顶级统计学期刊Journal of the American Statistical Association、Annals of Statistics、Journal of the Royal Statistical Society-Series B、Biometrika以及人工智能顶会NeurIPS上揭晓论文多篇。2018年入选国际统计学会推选会员(Elected member),2019年担当天下青年统计学家协会副会长以及天下统计课本编审委员会第七届委员会专业委员(数据科学与大数据手艺应用组),2020年担当第八届国务院学科评议组(统计学)成员,2022年担当天下应用统计专业硕士教指委委员,兼任国际统计学权威期刊Annals of Applied Statistics编委(Associate Editor)以及海内统计学权威期刊《统计研究》编委。
主讲内容:
In this paper, we propose a novel spatial-temporal model with individual random effects characterized by a location-scale structure, which allows us to flexibly capture the pure influence of space-specific factors in the framework of quantile regression.
A hybrid two-stage estimation procedure is introduced for this model, where the first stage proposes a Gaussian quasi-maximum likelihood estimator (QMLE) for the spatial-temporal effects while the second stage constructs a weighted conditional quantile estimator (WCQE) to study the conditional quantiles of the random effects related to space-specific attributes.
The validity of the two-stage hybrid estimation is verified, and the asymptotic properties of our estimators are established.
Our simulation study indicates that the proposed estimation procedure performs well in different scenarios with finite samples, and a real case study on the air quality of China is used to illustrate the application of the proposed method.