Spatial Regression Analysis Using Eigenvector Spatial Filtering

Erscheinungsjahr 2019
ISBN: 978-0-12-815043-6
Verlag: Elsevier Science Publishing Co Inc

Buch, Englisch, 286 Seiten, Format (B × H): 152 mm x 229 mm, Gewicht: 450 g

Spatial Regression Analysis Using Eigenvector Spatial Filtering provides theoretical foundations and guides practical implementation of the Moran eigenvector spatial filtering (MESF) technique. MESF is a novel and powerful spatial statistical methodology that allows spatial scientists to account for spatial autocorrelation in their georeferenced data analyses. Its appeal is in its simplicity, yet its implementation drawbacks include serious complexities associated with constructing an eigenvector spatial filter.

This book discusses MESF specifications for various intermediate-level topics, including spatially varying coefficients models, (non) linear mixed models, local spatial autocorrelation, space-time models, and spatial interaction models. Spatial Regression Analysis Using Eigenvector Spatial Filtering is accompanied by sample R codes and a Windows application with illustrative datasets so that readers can replicate the examples in the book and apply the methodology to their own application projects. It also includes a Foreword by Pierre Legendre.

Zielgruppe

<p>Graduate students and researchers worldwide working in spatial econometrics, spatial statistics, urban and regional economics, spatial data analysis, and more broadly from geography, GIS science, ecology, regional science, epidemiology and public health, economics, demography, applied statistics, remote sensing, urban and regional planning, transportation, and crime mapping. </p>

Autoren/Hrsg.

Griffith, Daniel

Chun, Yongwan

Li, Bin

Fachgebiete

• Wirtschaftswissenschaften Volkswirtschaftslehre Volkswirtschaftslehre Allgemein Ökonometrie
• Wirtschaftswissenschaften Volkswirtschaftslehre Volkswirtschaftslehre Allgemein Wirtschaftsstatistik, Demographie
• Wirtschaftswissenschaften Volkswirtschaftslehre Regional- und Städtische Wirtschaft

Inhaltsverzeichnis

1. Spatial autocorrelation2. An introduction to spectral analysis3. MESF and linear regression4. Software implementation for constructing an ESF, with special reference to linear regression5. MESF and generalized linear regression6. Modeling spatial heterogeneity with MESF7. Spatial interaction modeling 8. Space-time modeling9. MESF and multivariate statistical analysis10. Concluding comments: Toy dataset implementation demonstrations

Über Autor(innen)

Griffith, Daniel
Dr. Daniel A. Griffith is an Ashbel Smith Professor Emeritus of Geospatial Information Sciences at
the University of Texas at Dallas, United States; a past affiliated Professor in the College of Public
Health at the University of South Florida, United States; and an Adjunct Professor in the Department
of Resource Economics and Environmental Sociology at the University of Alberta, Canada. He
specializes in spatial statistics, quantitative-urban-economic geography, and urban public health.

Chun, Yongwan
Yongwan Chun is an Associate Professor of Geospatial Information Sciences at the University of Texas at Dallas. His research interests lie in spatial statistics and GIS, focusing on urban issues, including population movement, environment, health, and crime. His research has been supported by the US National Science Foundation, and the US National Institutes of Health, among others. He has over 50 publications, including books, journal articles, book chapters, and conference proceedings.

Li, Bin
Today, Dr. Li's research is focused on statistics and machine learning. He has published >75 peer reviewed research papers with >1,300 citations of his work.