Modelling Spatial Processes

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Spatial Econometrics: Methods and Models

Author: L. Anselin
language: en
Publisher: Springer Science & Business Media
Release Date: 2013-03-09
Spatial econometrics deals with spatial dependence and spatial heterogeneity, critical aspects of the data used by regional scientists. These characteristics may cause standard econometric techniques to become inappropriate. In this book, I combine several recent research results to construct a comprehensive approach to the incorporation of spatial effects in econometrics. My primary focus is to demonstrate how these spatial effects can be considered as special cases of general frameworks in standard econometrics, and to outline how they necessitate a separate set of methods and techniques, encompassed within the field of spatial econometrics. My viewpoint differs from that taken in the discussion of spatial autocorrelation in spatial statistics - e.g., most recently by Cliff and Ord (1981) and Upton and Fingleton (1985) - in that I am mostly concerned with the relevance of spatial effects on model specification, estimation and other inference, in what I caIl a model-driven approach, as opposed to a data-driven approach in spatial statistics. I attempt to combine a rigorous econometric perspective with a comprehensive treatment of methodological issues in spatial analysis.
Modelling Spatial Processes

A novel methodology is put forward in this book, which empowers researchers to investigate and identify potential spatial processes among a set of regions. Spatial processes and their underlying functional spatial relationships are commonly observed in the geosciences and related disciplines. Examples are spatially autocorrelated random variables manifesting themselves in distinct global patterns as well as local clusters and hot spots, or spatial interaction leading to stochastic ties among the regions. An example from observational epidemiology demonstrates the flexibility of Moran's approach by analyzing the spatial distribution of cancer data from several perspectives. Recent advances in computing technology, computer algorithms, statistical techniques and global and local spatial patterns by means of Moran's I feasability. Moran's I is an extremely versatile tool for exploring and analyzing spatial data and testing spatial hypotheses.
Models of Spatial Processes

Author: Arthur Getis
language: en
Publisher: Cambridge University Press
Release Date: 2008-12-11
This book approaches the study of patterns by emphasising the processes responsible for them; it emphasises the logical format of process-to-pattern rather than the more wasteful pattern-to-process approach. The concern is primarily with two-dimensional surfaces, which is the way most maps are used for analysis. The material is organised into sections on process models responsible for point patterns, for line patterns and then for area patterns. It represents a synthesis of the work done on patterns in a number of fields and a large literature is reviewed in the process of the synthesis. In many respects this book represents a translation of complex mathematical materials into a readable and relatively simple verbal approach to the subject and thus brings the more sophisticated aspects to a larger number of students than has been done before. The reader need only have an elementary background in statistics. The basic probability theory required by the text is given in an appendix.