Luc Anselin Highlighting the CUPPA Speaker Series

Date / Time

April 6, 2018

3:30 pm - 4:30 pm


Luc Anselin from the University of Chicago discusses his time-honored article on Local Indicators of Spatial Analysis in Geographical Analysis. Part of the CUPPA Speaker Series.

Lower Level
400 S. Peoria St. 
Friday April 6th 2018
3:30 – 4:30 p.m. 
Conversation, food & drink to follow

Luc Anselin is the Stein-Freiler Distinguished Service Professor of Sociology at the University of Chicago. He is the founding director of the Center for Spatial Data Science, a joint initiative of the Social Sciences Division and the Computation Institute, to advance computational and statistical methods of dealing with spatial data. Anselin also serves as a Senior Fellow of NORC and chairs the Committee on Geographical Sciences. He was elected to the National Academy of Sciences in 2008 and the American Academy of Arts and Sciences in 2011. His honors include the Walter Isard Award, the William Alonso Prize and the University Consortium for Geographic Information Science (UCGIS) Research Award.

It has been more than 20 years since the publication of the article on Local Indicators of Spatial Association (LISA) in Geographical Analysis (Anselin 1995). This article turned out to be one of the most cited and downloaded pieces in GA. Since its publication, the idea of a local indicator has led to a wide range of applications to spatial cluster and outlier detection, as well as to a considerable methodological literature dealing with extensions to different types of data (categorical, space-time), proper inference (the multiple comparison problem), and computational issues.

In this presentation, Anselin will start with a brief review of these developments, with a focus on inference and computational issues. He will then present some new results on a particular variant of LISA, the Local Geary statistic and generalize the univariate case to a Multivariate Indicator of Local Spatial Autocorrelation that takes the form of a multivariate Local Geary statistic. There will be additional discussion on the statistical properties, inference, visualization and interpretation, as well as an illustration using Guerry’s 1833 classic data set on moral statistics in France.

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