报告题目：Eigenvector Spatial Filtering: motivation, conceptualization, mathematics, and applications  

报 告 人：Professor Daniel A. Griffith, University of Texas at Dallas

报告摘要：Spatial autocorrelation is everywhere—it underlies art, is found in common games, allows such viewings as television, and can be the artifact of a particular zonation scheme. In its more serious form, it creates a number of challenges in science. Eigenvector spatial filtering is a powerful new methodology that addresses these scientific challenges by creating a synthetic proxy variable, a linear combination of eigenvectors extracted from a spatial connectivity matrix that ties geographic objects together in space, and then adding this proxy variate as a control variable to a model specification. This control variable, whose individual eigenvectors are distinct map patterns, identifies and isolates the stochastic spatial dependencies among georeferenced observations, thus allowing spatial analysis to proceed as if observations are independent. This presentation briefly outlines the motivation and development of this methodology, highlights some of its interesting mathematical aspects, and illustrates some of its advantages vis-à-vis popular spatial autoregressive model specifications.

主讲人简介：Dr. Daniel A. Griffith是 Ashbel Smith教授，现就职于美国得克萨斯州立大学经济政治政策学院，地理学顶尖学术期刊《Geographical Analysis》编辑，国际地理学会系统建模委员会委员，美国统计协会研究员、德国马普学会人口研究所的访问学者、富布赖特研究员、古根海姆研究员、纽约科学院院士，空间计量经济学协会的创始会员之一、北美区域科学委员会前任会长。 在2005年到德州达拉斯大学任教前，他曾在瑞尔森科技大学、SUNY/Buffalo大学、迈阿密大学任教。还曾在美国俄勒冈州立大学、鹿特丹大学、罗马大学、剑桥大学任客座教授。 Dr. Daniel A. Griffith在大学主讲过的课程有空间统计、地理信息科学的研究与设计、数理统计、空间数据组织和概念等。主要研究领域包括空间统计、空间计量经济学、应用统计。已出版17本专著，发表200余篇论文。

主 持 人：王劲峰 研究员

报告时间：2013年5月28日 下午16:00-18:00

地        点：中科院地理资源所2321报告厅