Morphisms for Quantitative Spatial Analysis
by Daniel A. Griffith (Author), Jean H. P. Paelinck (Author)

About the Author
Daniel A. Griffith, an Ashbel Smith Professor of Geospatial Information Science at the University of Texas at Dallas, TX, USA, has published 18 books and over 200 articles appearing in geography, statistics, mathematics, economics, and regional science journals and other outlets. Griffith served as editor of Geographical Analysis from 2009 to 2014. Among his many awards, he is a fellow of the Royal Society of Canada, the American Statistical Association, and the Guggenheim Foundation.
Jean H. P. Paelinck is an emeritus professor of the Erasmus University Rotterdam, and most recently was a distinguished Visiting Professor at George Mason University, VA, USA. As a (co-)author and (co-)editor, he has published around fifty volumes and over 400 articles, mainly on theoretical spatial economics and spatial econometrics. Paelinck has been awarded seven honorary PhDs and numerous other international distinctions, e.g. the Walter Isard Award in Regional Science.

About this book
This book treats the notion of morphisms in spatial analysis, paralleling these concepts in spatial statistics (Part I) and spatial econometrics (Part II). The principal concept is morphism (e.g., isomorphisms, homomorphisms, and allomorphisms), which is defined as a structure preserving the functional linkage between mathematical properties or operations in spatial statistics and spatial econometrics, among other disciplines. The purpose of this book is to present selected conceptions in both domains that are structurally the same, even though their labelling and the notation for their elements may differ. As the approaches presented here are applied to empirical materials in geography and economics, the book will also be of interest to scholars of regional science, quantitative geography and the geospatial sciences. It is a follow-up to the book “Non-standard Spatial Statistics and Spatial Econometrics” by the same authors, which was published by Springer in 2011.

Brief contents
Part I Spatial Statistics
1 Introduction to Part I: Spatial Statistics 3
2 Spatial Autocorrelation and the p-Median Problem. 9
3 Space–Time Autocorrelation 25
4 The Relative Importance of Spatial and Temporal Autocorrelation 35
5 The Spatial Weights Matrix and ESF 49
6 Clustering: Spatial Autocorrelation and Location Quotients 61
7 Spatial Autocorrelation Parameter Estimation for Massively Large Georeferenced Datasets 73
8 Space–Time Data and Semi-saturated Fixed Effects 89
9 Spatial Autocorrelation and Spatial Interaction Gravity Models. 99
10 General Conclusions About Spatial Statistics 113
Part II Spatial Econometrics
11 Introduction to Part II: Spatial Econometrics 125
12 Tinbergen–Bos Systems: Combining Combinatorial Analysis with Metric Topology 127
13 Time, Space, or Econotimespace? 149
14 Hybrid Dynamical Systems and Control 167
15 The W Matrix Revisited 177
16 Clustering: Some Nonstandard Approaches 187
17 Linear Expenditure Systems and Related Estimation Problems 201
18 Structural Indicators Galore. 215
19 Traveling with the Salesman... 227
20 Complexer and Complexer, Said Alice 237
21 General Conclusions About Spatial Econometrics 255
Epilogue 259
Author Index 261
Subject Index 265

Series: Advanced Studies in Theoretical and Applied Econometrics (Book 51)
Pages: 258 pages
Publisher: Springer; 1st ed. 2018 edition (March 8, 2018)
Language: English
ISBN-10: 3319725521
ISBN-13: 978-3319725529