- 演讲人: 杨立坚教授(清华大学统计研究中心)
- 时间:2019年06月21日 星期五 上午10:00-
- 地点:紫金港校区管理学院行政楼14楼1417报告厅
- 主办单位:浙江大学数据科学研究中心、浙江大学数学科学学院统计学研究所
摘要:In many application areas, data are collected on a count or binary response with spatial covariate information. In this article, we introduce a new class of generalized geoadditive models (GGAMs) for spatial data distributed over complex domains. Through a link function, the proposed GGAM assumes that the mean of the discrete response variable depends on additive univariate functions of explanatory variables and a bivariate function to adjust for the spatial effect. We propose a two-stage approach for estimating and making inferences of the components in the GGAM. In the first stage, the univariate components and the geographical component in the model are approximated via univariate polynomial splines and bivariate penalized splines over triangulation, respectively. In the second stage, local polynomial smoothing is applied to the cleaned univariate data to average out the variation of the first-stage estimators. We investigate the consistency of the proposed estimators and the asymptotic normality of the univariate components. We also establish the simultaneous confidence band for each of the univariate components. The performance of the proposed method is evaluated by two simulation studies. We apply the proposed method to analyze the crash counts data in the Tampa-St. Petersburg urbanized area in Florida.
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联系人: 张立新教授 stazlx@zju.edu.cn
浙江大学数据科学研究中心、浙江大学数学科学学院统计学研究所
报告人简介:
杨立坚, 清华大学长聘教授、中组部国家特聘专家。 1987年获北京大学数学理学士,1995年获北卡罗来纳大学教堂山分校(University of North Carolina at Chapel Hill)统计博士,1995-1997年在柏林洪堡大学(Humboldt Universität zu Berlin)从事统计与计量经济学博士后研究。历任密西根州立大学统计与概率系(Michigan State University Department of Statistics and Probability)助理教授(1997-2001)、终身副教授(2001-2006)、终身正教授(2006-2014)、研究生主任(Graduate Director, 2007-2010),苏州大学特聘教授、高等统计与计量经济中心主任期间(2011-2016)。 先后当选为国际统计学会会员(Elected Member, International Statistical Institute),美国统计协会会士(Elected Fellow, American Statistical Association),国际数理统计学会会士(Elected Fellow, Institute of Mathematical Statistics)。 曾任统SCI期刊《Computational Statistics》、《Statistica Sinica》、《Journal of Nonparametric Statistics》、《Journal of Business and Economic Statistics》副编审(Associate Editor)和《Sankhyā》 正编审(Editor)。研究方向包括时间序列,函数型及高维数据的统计推断,以及统计学对经济学、金融学、农学、食品科学、地理学和遗传学的应用。