Spatial Regression Analysis Using Eigenvector Spatial Filtering - Couverture souple

Griffith, Daniel A.; Chun, Yongwan; Li, Bin

Couverture souple

ISBN 10 : 0128150432 ISBN 13 : 9780128150436

Editeur : Academic Press Inc, 2019

Synopsis

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.

A propos du livre

À propos des auteurs

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.

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.

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.

Détails de l'édition

• Éditeur: Academic Press Inc
• Date d'édition: 2019
• Langue: anglais
• ISBN 10: 0128150432
• ISBN 13: 9780128150436
• Reliure: Broché
• Nombre de pages: 286
• Coordonnées du fabricant: non disponible
• Personne responsable: Yeepin GmbH; 492000000000; sunshine12232@outlook.com; ; Alleestr.11; Kaiserslautern; Rheinland-Pfalz; 67655; Allemagne