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Books in General spatial economics

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    • Spatial Regression Analysis Using Eigenvector Spatial Filtering

      • 1st Edition
      • Daniel Griffith + 2 more
      • English
      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.

    • Spatial Choices and Processes

      • 1st Edition
      • M.M. Fischer + 2 more
      • English
      Spatial decisions and processes are fundamental to the understanding of spatial structure. In the earlier stages of spatial analysis proposed explanations were typically on the aggregate, phenomenological level. Now a new field has evolved and matured which calls for a deeper understanding of spatial structure with a particular emphasis on spatial decisions and processes. The present volume serves as a guide and as an anthology by discussing a wide variety of new modelling approaches, techniques and issues related to spatial decision and processes and drawing these seemingly disparate, but interlocking parts together.

    • The Economics of Complex Spatial Systems

      • 1st Edition
      • A. Reggiani + 1 more
      • English
      This book argues that complexity theory offers new departures for (spatial-) economic modelling. It offers a broad overview of recent advances in non-linear dynamics (catastrophe theory, chaos theory, evolutionary theory and so forth) and illustrates the relevance of this new paradigm on the basis of several illustrations in the area of space-economy. The empirical limitations - inherent in the use of non-linear dynamic systems approaches - are also addressed. Next, the application potential of biocomputing (in particular, neural networks and evolutionary algorithms) is stressed, while various empirical model results are presented. The book concludes with an agenda for further research.