Spatial Regression Analysis Using Eigenvector Spatial Filtering (Paperback)

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.

General

Imprint:	Academic Press Inc
Country of origin:	United States
Release date:	September 2019
First published:	2019
Authors:	Daniel A. Griffith • Yongwan Chun • Bin Li
Dimensions:	229 x 152mm (L x W)
Format:	Paperback
Pages:	286
ISBN-13:	978-0-12-815043-6
Categories:	Books > Reference & Interdisciplinary > Communication studies > Data analysis Books > Business & Economics > Economics > General Books > Social sciences > Sociology, social studies > Social groups & communities > Urban communities Books > Earth & environment > Geography > Cartography, geodesy & geographic information systems (GIS) > Geographical information systems (GIS) Books > Earth & environment > Geography > Cartography, geodesy & geographic information systems (GIS) > Remote sensing Books > Computing & IT > Computer software packages > Other software packages > Mathematical & statistical software Promotions
LSN:	0-12-815043-2
Barcode:	9780128150436

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