Comparer des méthodes
Examinez les méthodes sélectionnées côte à côte ; les lignes qui diffèrent sont mises en évidence.
| Krigage Universel de Panneau× | Kriging Ordinaire× | |
|---|---|---|
| Domaine | Analyse spatiale | Analyse spatiale |
| Famille | Regression model | Regression model |
| Année d'origine≠ | 1963 (base method); panel extension: 1990s–2000s | 1963 |
| Auteur d'origine≠ | Matheron, G.; extended to panel settings by geostatistical literature | Georges Matheron (formalising D.G. Krige's empirical work) |
| Type | Geostatistical interpolation | Geostatistical interpolation |
| Source fondatrice≠ | Matheron, G. (1963). Principles of geostatistics. Economic Geology, 58(8), 1246–1266. DOI ↗ | Matheron, G. (1963). Principles of geostatistics. Economic Geology, 58(8), 1246-1266. DOI ↗ |
| Alias | UK panel interpolation, panel UK, universal kriging for panel data, longitudinal universal kriging | OK, kriging interpolation, geostatistical interpolation, BLUE spatial predictor |
| Apparentées≠ | 5 | 4 |
| Résumé≠ | Panel Universal Kriging extends Universal Kriging to data structures with repeated spatial observations over time (panel or longitudinal format). It simultaneously estimates a deterministic trend surface — incorporating covariates that vary across both space and time — and a stochastic spatially correlated residual, pooling information across all time periods to improve prediction accuracy and parameter stability. | 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. |
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