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| التوزيع الكريجي الشامل المحلي× | الانحدار الموزون جغرافيًا (GWR)× | |
|---|---|---|
| المجال | التحليل المكاني | التحليل المكاني |
| العائلة | Regression model | Regression model |
| سنة النشأة≠ | 1969/1997 | 2002 |
| صاحب الطريقة≠ | Matheron, G. (trend/drift kriging); local neighborhood approach standard in geostatistical practice | Fotheringham, Brunsdon & Charlton |
| النوع≠ | Spatial interpolation model | Local spatial regression |
| المصدر التأسيسي≠ | Goovaerts, P. (1997). Geostatistics for Natural Resources Evaluation. Oxford University Press. ISBN: 9780195115383 | Fotheringham, A. S., Brunsdon, C., & Charlton, M. (2002). Geographically Weighted Regression: The Analysis of Spatially Varying Relationships. Wiley. ISBN: 978-0471496168 |
| الأسماء البديلة | local UK, local kriging with trend, local KED, local kriging with external drift | GWR, local regression, spatially varying coefficient regression, Coğrafi Ağırlıklı Regresyon (GWR) |
| ذات صلة | 5 | 5 |
| الملخص≠ | Local Universal Kriging is a geostatistical interpolation method that combines a spatially varying deterministic trend with a stochastic residual, estimated using only nearby observations within a defined search neighborhood. It generalizes local ordinary kriging by explicitly modeling and removing a polynomial or covariate-driven drift before interpolating the residual surface. | 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. |
| ScholarGateمجموعة البيانات ↗ |
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