| Online-Ressource |
Verfasst von: | Fotheringham, Alexander Stewart [VerfasserIn] |
| Oshan, Taylor M. [VerfasserIn] |
| Li, Ziqi [VerfasserIn] |
Titel: | Multiscale geographically weighted regression |
Titelzusatz: | theory and practice |
Verf.angabe: | A. Stewart Fotheringham, Taylor M. Oshan, and Ziqi Li |
Ausgabe: | First edition |
Verlagsort: | Boca Raton ; London ; New York |
Verlag: | CRC Press |
Jahr: | 2024 |
Umfang: | 1 Online-Ressource (xvii, 176 Seiten) |
Fussnoten: | Includes bibliographical references and index |
ISBN: | 978-1-003-43546-4 |
Abstract: | "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 serves as definitive guide to local regression modeling and the analysis of spatially varying processes, a very cutting-edge, hands-on, and innovative resource. The authors start 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 also provided, as well as an analysis of the 2020 US Presidential election"-- |
| Introduction to local modeling -- MGWR : the essentials -- Inference -- Spatial scale and local modeling -- Software for MGWR -- Caveat emptor! -- A local analysis of voting behavior : the 2020 US presidential election -- MGWR and other models incorporating spatial contextual effects. |
DOI: | doi:10.1201/9781003435464 |
URL: | Resolving-System: https://doi.org/10.1201/9781003435464 |
| Verlag: https://www.taylorfrancis.com/books/9781003435464 |
| DOI: https://doi.org/10.1201/9781003435464 |
Schlagwörter: | (s)Geografie / (s)Regressionsmodell / (s)Mehrskalenmodell |
Datenträger: | Online-Ressource |
Sprache: | eng |
Bibliogr. Hinweis: | Erscheint auch als : Druck-Ausgabe: Fotheringham, Alexander Stewart, 1954 - : Multiscale geographically weighted regression. - First edition. - Boca Raton : CRC Press, 2024. - xvii, 176 Seiten |
Sach-SW: | TECHNOLOGY / Remote Sensing |
| SCIENCE / Earth Sciences / Geography |
| COMPUTERS / Data Modeling & Design |
K10plus-PPN: | 1873206119 |
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Lokale URL UB: | Zum Volltext |
Multiscale geographically weighted regression / Fotheringham, Alexander Stewart [VerfasserIn]; 2024 (Online-Ressource)