مقایسهٔ روشها
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| کریجینگ معمولی× | رگرسیون وزنی جغرافیایی (GWR)× | |
|---|---|---|
| حوزه | تحلیل فضایی | تحلیل فضایی |
| خانواده | Regression model | Regression model |
| سال پیدایش≠ | 1963 | 2002 |
| پدیدآور≠ | Georges Matheron (formalising D.G. Krige's empirical work) | Fotheringham, Brunsdon & Charlton |
| نوع≠ | Geostatistical interpolation | Local spatial regression |
| منبع بنیادین≠ | Matheron, G. (1963). Principles of geostatistics. Economic Geology, 58(8), 1246-1266. DOI ↗ | Fotheringham, A. S., Brunsdon, C., & Charlton, M. (2002). Geographically Weighted Regression: The Analysis of Spatially Varying Relationships. Wiley. ISBN: 978-0471496168 |
| نامهای دیگر | OK, kriging interpolation, geostatistical interpolation, BLUE spatial predictor | GWR, local regression, spatially varying coefficient regression, Coğrafi Ağırlıklı Regresyon (GWR) |
| مرتبط≠ | 4 | 5 |
| خلاصه≠ | Ordinary Kriging (OK) is the standard geostatistical method for interpolating a continuous spatial variable at unsampled locations. It derives optimal, unbiased weights from the spatial covariance structure of the data, making it the Best Linear Unbiased Predictor (BLUP) under stationarity assumptions. Unlike simpler distance-based methods, it also provides a prediction uncertainty (kriging variance) at every interpolated point. | 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. |
| ScholarGateمجموعهداده ↗ |
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