Geographically weighted regression and multicollinearity: dispelling the myth

Geographically weighted regression (GWR) extends the familiar regression framework by estimating a set of parameters for any number of locations within a study area, rather than producing a single parameter estimate for each relationship specified in the model. Recent literature has suggested that G...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	Journal of geographical systems Jg. 18; H. 4; S. 303 - 329
Hauptverfasser:	Fotheringham, A. Stewart, Oshan, Taylor M.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Berlin/Heidelberg Springer Berlin Heidelberg 01.10.2016 Springer Springer Nature B.V
Schlagworte:	Analysis Bandwidths Computer Appl. in Social and Behavioral Sciences Computer simulation Econometrics Economics Economics and Finance Estimates Estimating Geographic information systems Geographical Information Systems/Cartography Geography Geospatial data Indicators Landscape/Regional and Urban Planning Lung cancer Mathematical models Original Article Parameter estimation Parameters Regional/Spatial Science Regression Studies Urban Economics Variables C52 Model evaluation, validation, and selection Collinearity GWR Regression diagnostics C18 Methodological issues: general Geographically weighted regression
ISSN:	1435-5930, 1435-5949
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!