Spatial Regression Analysis Using Eigenvector Spatial Filtering
  • Author : Daniel Griffith
  • Release Date : 14 September 2019
  • Publisher : Academic Press
  • Genre : Business & Economics
  • Pages : 286
  • ISBN 13 : 9780128156926

Spatial Regression Analysis Using Eigenvector Spatial Filtering Book Summary

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. Reviews the uses of ESF across linear regression, generalized linear regression, spatial autocorrelation measurement, and spatially varying coefficient models Includes computer code and template datasets for further modeling Provides comprehensive coverage of related concepts in spatial data analysis and spatial statistics

Spatial Regression Analysis Using Eigenvector Spatial Filtering

Spatial Regression Analysis Using Eigenvector Spatial Filtering

Author : Daniel Griffith,Yongwan Chun,Bin Li
Publisher : Academic Press
Genre : Business & Economics
Total View : 7909 Views
File Size : 44,5 Mb
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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 ...

Spatial Regression Analysis Using Eigenvector Spatial Filtering

Spatial Regression Analysis Using Eigenvector Spatial Filtering

Author : Daniel Griffith,Yongwan Chun,Bin Li
Publisher : Academic Press
Genre : Business & Economics
Total View : 1707 Views
File Size : 55,7 Mb
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Spatial Regression Analysis Using Eigenvector Spatial Filtering provides both theoretical foundations and guidance on practical implementation for the eigenvector spatial filtering (ESF) technique. ESF is a novel and powerful spatial statistical methodology that allows spatial scientists to account for spatial autocorrelation in georeferenced data analyses. With its flexible structure, ESF ...

Spatial Autocorrelation and Spatial Filtering

Spatial Autocorrelation and Spatial Filtering

Author : Daniel A. Griffith
Publisher : Springer Science & Business Media
Genre : Science
Total View : 8460 Views
File Size : 42,8 Mb
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Scientific visualization may be defined as the transformation of numerical scientific data into informative graphical displays. The text introduces a nonverbal model to subdisciplines that until now has mostly employed mathematical or verbal-conceptual models. The focus is on how scientific visualization can help revolutionize the manner in which the tendencies ...

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Publisher : John Wiley & Sons
Genre : Science
Total View : 6194 Views
File Size : 40,5 Mb
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Publisher : Cambridge University Press
Genre : Reference
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Publisher : Springer Science & Business Media
Genre : Business & Economics
Total View : 6869 Views
File Size : 51,9 Mb
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The Handbook is written for academics, researchers, practitioners and advanced graduate students. It has been designed to be read by those new or starting out in the field of spatial analysis as well as by those who are already familiar with the field. The chapters have been written in such ...

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Author : Griffith, Daniel A.,Li, Bin
Publisher : Edward Elgar Publishing
Genre : Social Science
Total View : 8456 Views
File Size : 40,8 Mb
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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 ...