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| Interpolation spatiale par krigeage× | Modèle de données de panel spatial (effets fixes/aléatoires)× | |
|---|---|---|
| Domaine | Analyse spatiale | Analyse spatiale |
| Famille | Regression model | Regression model |
| Année d'origine≠ | 1963 | 2014 |
| Auteur d'origine≠ | Georges Matheron (formalised geostatistics) | Elhorst; Lee & Yu |
| Type≠ | Geostatistical spatial interpolation | Spatial econometric panel model |
| Source fondatrice≠ | Matheron, G. (1963). Principles of Geostatistics. Economic Geology, 58(8), 1246–1266. DOI ↗ | Elhorst, J. P. (2014). Spatial Econometrics: From Cross-Sectional Data to Spatial Panels. Springer. DOI ↗ |
| Alias | geostatistical interpolation, Gaussian process regression (geostatistics), ordinary kriging, Kriging (Mekânsal Enterpolasyon) | spatial panel FE/RE, spatial econometric panel, spatial lag/error panel, Uzamsal Panel Modeli (Spatial Panel FE/RE) |
| Apparentées≠ | 5 | 4 |
| Résumé≠ | Kriging is a geostatistical method that predicts the value of a continuous variable at unmeasured locations from nearby measurements, using the spatial correlation structure captured by a variogram. Formalised by Georges Matheron in 1963, it is the best linear unbiased predictor (BLUP) for spatial data and comes in Ordinary, Universal, and Co-Kriging forms. | The spatial panel model is a family of econometric models that adds spatial dependence to panel data (units observed over time). It combines fixed- or random-effects panel structure with spatial lag, spatial error, or spatial Durbin components, and is developed in the modern spatial-econometrics literature by Elhorst (2014) and Lee & Yu (2010). |
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