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Geographical Weighted Regression (GWR) is a new local modellingtechnique for analysing spatial analysis. This technique allowslocal as opposed to global models of relationships to be measuredand mapped. This is the first and only book on this technique,offering comprehensive coverage on this new 'hot' topic in spatialanalysis. * Provides step-by-step examples of how to use the GWR model usingdata sets and examples on issues such as house price determinants,educational attainment levels and school performance statistics * Contains a broad discussion of and basic concepts on GWR throughto ideas…mehr
Geographical Weighted Regression (GWR) is a new local modellingtechnique for analysing spatial analysis. This technique allowslocal as opposed to global models of relationships to be measuredand mapped. This is the first and only book on this technique,offering comprehensive coverage on this new 'hot' topic in spatialanalysis. * Provides step-by-step examples of how to use the GWR model usingdata sets and examples on issues such as house price determinants,educational attainment levels and school performance statistics * Contains a broad discussion of and basic concepts on GWR throughto ideas on statistical inference for GWR models * uniquely features accompanying author-written software thatallows users to undertake sophisticated and complex forms of GWRwithin a user-friendly, Windows-based, front-end (see book fordetails).
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Autorenporträt
A. Stewart Fotheringham, Professor of Quantitative Geography, University of Newcastle. Chris Brunsdon, Senior Lecturer in Spatial Analysis, University of Newcastle. Martin Charlton, Lecturer in Geographical Information Systems, University of Newcastle.
Inhaltsangabe
Acknowledgements xi 1. Local Statistics and Local Models for Spatial Data 1 2. Geographically Weighted Regression: The Basics 27 3. Extensions to the Basic GWR Model 65 4. Statistical Inference and Geographically Weighted Regression 83 5. GWR and Spatial Autocorrelation 103 6. Scale Issues and Geographically Weighted Regression 127 7. Geographically Weighted Local Statistics 159 8. Extensions of Geographically Weighting 187 9. Software for Geographically Weighted Regression 207 Epilogue 241 Bibliography 255 Index 267
Acknowledgements xi 1. Local Statistics and Local Models for Spatial Data 1 2. Geographically Weighted Regression: The Basics 27 3. Extensions to the Basic GWR Model 65 4. Statistical Inference and Geographically Weighted Regression 83 5. GWR and Spatial Autocorrelation 103 6. Scale Issues and Geographically Weighted Regression 127 7. Geographically Weighted Local Statistics 159 8. Extensions of Geographically Weighting 187 9. Software for Geographically Weighted Regression 207 Epilogue 241 Bibliography 255 Index 267