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| Product ID: | 9781032564227 |
| Product Form: | Hardback |
| Country of Manufacture: | GB |
| Title: | Multiscale Geographically Weighted Regression |
| Subtitle: | Theory and Practice |
| Authors: | Author: A. Stewart Fotheringham, Ziqi Li, Taylor M. Oshan |
| Page Count: | 176 |
| Subjects: | Probability and statistics, Probability & statistics, Human geography, Geographical information systems, geodata and remote sensing, Environmental science, engineering and technology, Agricultural science, Information technology: general topics, Computer science, Human geography, Geographical information systems (GIS) & remote sensing, Environmental science, engineering & technology, Agricultural science, Information technology: general issues, Computer science |
| Description: | Select Guide Rating Multiscale Geographically Weighted Regression (MGWR) is an important method for exploring spatial heterogeneity and modelling local spatial processes in spatial analysis. This book introduces and explains how to model continuous spatial processes within a regression framework, and serves as a hands-on resource for students and researchers. Multiscale geographically weighted regression (MGWR) is an important method that is used across many disciplines for exploring spatial heterogeneity and modeling local spatial processes. This book introduces the concepts behind local spatial modeling and explains how to model heterogeneous spatial processes within a regression framework. It starts with the basic ideas and fundamentals of local spatial modeling followed by a detailed discussion of scale issues and statistical inference related to MGWR. A comprehensive guide to free, user-friendly, software for MGWR is provided, as well as an example of the application of MGWR to understand voting behavior in the 2020 US Presidential election. Multiscale Geographically Weighted Regression: Theory and Practice is the definitive guide to local regression modeling and the analysis of spatially varying processes, a very cutting-edge, hands-on, and innovative resource. Features
The book is ideal for senior undergraduate and graduate students in advanced spatial analysis and GIS courses taught in any spatial science discipline as well as for researchers, academics, and professionals who want to understand how location can affect human behavior through local regression modeling. |
| Imprint Name: | CRC Press |
| Publisher Name: | Taylor & Francis Ltd |
| Country of Publication: | GB |
| Publishing Date: | 2023-11-15 |
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