Comparer des méthodes

	Krigage global	Kriging Ordinaire
Domaine	Analyse spatiale	Analyse spatiale
Famille	Regression model	Regression model
Année d'origine	1960s–1993	1963
Auteur d'origine	Georges Matheron (kriging framework); global neighborhood usage formalized in applied geostatistics	Georges Matheron (formalising D.G. Krige's empirical work)
Type	Geostatistical interpolation	Geostatistical interpolation
Source fondatrice	Cressie, N. A. C. (1993). Statistics for Spatial Data (revised ed.). Wiley-Interscience. ISBN: 978-0471002550	Matheron, G. (1963). Principles of geostatistics. Economic Geology, 58(8), 1246-1266.
Alias	global-neighborhood kriging, full-data kriging, exhaustive kriging, non-local kriging	OK, kriging interpolation, geostatistical interpolation, BLUE spatial predictor
Apparentées	5	4
Résumé	Global Kriging is the ordinary kriging interpolation procedure applied using all available sample points as the neighborhood — no spatial search window limits which data contribute to each prediction. It produces optimal linear unbiased predictions of an unobserved value at any target location, with associated prediction-error variances, by exploiting a fitted variogram model that encodes spatial autocorrelation across the entire dataset.	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.