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| Lokale Ordinary Kriging-Interpolation× | Geographisch gewichtete Regression (GWR)× | |
|---|---|---|
| Fachgebiet | Räumliche Analyse | Räumliche Analyse |
| Familie | Regression model | Regression model |
| Entstehungsjahr≠ | 1970s–1990s | 2002 |
| Urheber≠ | Journel & Huijbregts; developed further by Goovaerts and Chiles & Delfiner | Fotheringham, Brunsdon & Charlton |
| Typ≠ | Geostatistical interpolation (local/moving-window variant) | Local spatial regression |
| Wegweisende Quelle≠ | Chiles, J.-P., & Delfiner, P. (1999). Geostatistics: Modeling Spatial Uncertainty. Wiley. ISBN: 978-0471083153 | Fotheringham, A. S., Brunsdon, C., & Charlton, M. (2002). Geographically Weighted Regression: The Analysis of Spatially Varying Relationships. Wiley. ISBN: 978-0471496168 |
| Aliasnamen | moving window kriging, local kriging, neighborhood kriging, LOK | GWR, local regression, spatially varying coefficient regression, Coğrafi Ağırlıklı Regresyon (GWR) |
| Verwandt | 5 | 5 |
| Zusammenfassung≠ | Local Ordinary Kriging (LOK) is a geostatistical interpolation method that estimates values at unsampled locations using only a spatially defined moving neighborhood of nearby observations. By restricting each prediction to a local data window rather than the full dataset, LOK accommodates spatial non-stationarity, reduces computational cost, and often yields more accurate local predictions than global ordinary kriging. | Geographically Weighted Regression is a local regression method, introduced by Fotheringham, Brunsdon and Charlton (2002), that allows the regression coefficients to vary across space. Instead of one global equation, it fits a separate set of coefficients at every location, capturing spatial heterogeneity in the relationships. |
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