Advanced Introduction to Spatial Statistics

Elgar Advanced Introductions series

Daniel A. Griffith, Ashbel Smith Professor of Geography and Geospatial Information Science, School of Economic, Political, and Policy Sciences, University of Texas at Dallas and Bin Li, Professor of Geography, Department of Geography and Environmental Studies, Central Michigan University, US

This Advanced Introduction provides a critical review and discussion of research concerning spatial statistics, differentiating between it and spatial econometrics, to answer a set of core questions covering the geographic-tagging-of-data origins of the concept and its theoretical underpinnings, conceptual advances, and challenges for future scholarly work. It offers a vital tool for understanding spatial statistics and surveys how concerns about violating the independent observations assumption of statistical analysis developed into this discipline.

随着越来越普遍和georef可用erenced data, this book offers a timely assessment of contemporary methods, models, and metrics—such as the eigenvector spatial filtering approach to handling spatial autocorrelation—in spatial statistics. I salute the authors for this enlightening contribution! The book will greatly empower us to better uncover mechanisms behind georeferenced data.’
– Li An, San Diego State University, US