Isbn: 9781032564234 - multiscale geographically weighted regression: theory and practice (9 risultati)

Condizione: New.

PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

Paperback. Condizione: Brand New. 176 pages. 6.14x0.42x9.21 inches. In Stock.

Condizione: New.

Taschenbuch. Condizione: Neu. Neuware - 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 - Provides a balance between conceptual and technical introduction to local models - Explains state-of-the-art spatial analysis technique for multiscale regression modeling - Describes best practices and provides a detailed walkthrough of freely available software, through examples and comparisons with other common spatial data modeling techniques - Includes a detailed case study to demonstrate methods and software - Takes a new and exciting angle on local spatial modeling using MGWR, an innovation to the previous local modeling 'bible' GWR 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.…

Paperback. Condizione: new. Paperback. 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.FeaturesProvides a balance between conceptual and technical introduction to local modelsExplains state-of-the-art spatial analysis technique for multiscale regression modelingDescribes best practices and provides a detailed walkthrough of freely available software, through examples and comparisons with other common spatial data modeling techniquesIncludes a detailed case study to demonstrate methods and softwareTakes a new and exciting angle on local spatial modeling using MGWR, an innovation to the previous local modeling bible GWRThe 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. 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. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Paperback. Condizione: new. Paperback. 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.FeaturesProvides a balance between conceptual and technical introduction to local modelsExplains state-of-the-art spatial analysis technique for multiscale regression modelingDescribes best practices and provides a detailed walkthrough of freely available software, through examples and comparisons with other common spatial data modeling techniquesIncludes a detailed case study to demonstrate methods and softwareTakes a new and exciting angle on local spatial modeling using MGWR, an innovation to the previous local modeling bible GWRThe 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. 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. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…

Paperback. Condizione: new. Paperback. 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.FeaturesProvides a balance between conceptual and technical introduction to local modelsExplains state-of-the-art spatial analysis technique for multiscale regression modelingDescribes best practices and provides a detailed walkthrough of freely available software, through examples and comparisons with other common spatial data modeling techniquesIncludes a detailed case study to demonstrate methods and softwareTakes a new and exciting angle on local spatial modeling using MGWR, an innovation to the previous local modeling bible GWRThe 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. 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. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…