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Modern Spatial Econometrics in Practice: A Guide to Geoda, Geodaspace and Pysal
Click to zoom the image Modern Spatial Econometrics in Practice: A Guide to Geoda, Geodaspace and Pysal
Publisher:Geoda Press LLC
Publication Date:2014-12-27
ISBN-10:0986342106
ISBN-13:9780986342103
Number of Pages:394 Pages
Book Type:Paperback
Weight:725 gram
Format of ebooks: PDF(Acrobat Reader) or Word version doc Document
Brief introduction of ebooks
Modern Spatial Econometrics in Practice: A Guide to Geoda, Geodaspace and Pysal


This book is the definitive user's guide to the spatial regression functionality in the software packages GeoDa and GeoDaSpace, as well as the spreg module in the PySAL library --all developed at the GeoDa Center for Geospatial Analysis and Computation. The book provides the techniques to test for and estimate spatial effects in linear regression models, addressing both spatial dependence (spatial autoregressive models) as well as spatial heterogeneity (spatial regimes models). The book also serves as an introduction and a practical guide to spatial econometrics in that it covers the methodological principles and formal results that underlie the various estimation methods, test procedures and model characteristics computed by the software. While the classical maximum likelihood estimation is included, the book's coverage emphasizes Modern techniques based on the principle of generalized method of moments (GMM).
Abstract
This book is the definitive user's guide to the spatial regression functionality in the software packages GeoDa and GeoDaSpace, as well as the spreg module in the PySAL library --all developed at the GeoDa Center for Geospatial Analysis and Computation. The book provides the techniques to test for and estimate spatial effects in linear regression models, addressing both spatial dependence (spatial autoregressive models) as well as spatial heterogeneity (spatial regimes models). The book also serves as an introduction and a practical guide to spatial econometrics in that it covers the methodological principles and formal results that underlie the various estimation methods, test procedures and model characteristics computed by the software. While the classical maximum likelihood estimation is included, the book's coverage emphasizes Modern techniques based on the principle of generalized method of moments (GMM).

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