Morphisms for Quantitative Spatial Analysis

• Κύριοι συγγραφείς: Griffith, Daniel A. (Συγγραφέας, http://id.loc.gov/vocabulary/relators/aut), Paelinck, Jean H. P. (http://id.loc.gov/vocabulary/relators/aut)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2018.
• Έκδοση: 1st ed. 2018.
• Σειρά: Advanced Studies in Theoretical and Applied Econometrics, 51
• Θέματα: Econometrics.; Geographical information systems.; Statistics .; Regional economics.; Spatial economics.; Geographical Information Systems/Cartography.; Statistics for Social Sciences, Humanities, Law.; Regional/Spatial Science.; Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences.; Humanities and Social Sciences, multidisciplinary.

 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. . 

 Preamble -- Introduction to Part 1: Spatial statistics -- Spatial autocorrelation and the p-Median problem -- Space-time autocorrelation -- The relative importance of spatial and temporal autocorrelation -- The spatial weights matrix and ESF -- Clustering: Spatial autocorrelation and location quotients -- Spatial autocorrelation parameter estimation for massively large georeferenced datasets -- Space-time data and semi-saturated fixed effects -- Spatial autocorrelation and spatial interaction gravity models -- General conclusions about spatial statistics -- Introduction to Part 2: Spatial econometrics -- Tinbergen-Bos systems: Combining combinatorial analysis with metric topology -- Time, space, or econotimespace?- Hybrid dynamical systems and control -- The W matrix revisited -- Clustering, some non-standard approaches -- Linear expenditure systems and related estimation problems -- Structural indicators galore -- Traveling with the salesman -- Complexer and complexer, said Alice -- General conclusions about spatial econometrics -- Epilogue -- References -- Subject index -- Author's index.