Módszerek összehasonlítása

	Tér-Idő Kriging	Ordinary Kriging
Tudományterület	Térbeli elemzés	Térbeli elemzés
Módszercsalád	Regression model	Regression model
Keletkezés éve	1999	1963
Megalkotó	Cressie & Huang; Kyriakidis & Journel	Georges Matheron (formalising D.G. Krige's empirical work)
Típus	Geostatistical interpolation	Geostatistical interpolation
Alapmű	Cressie, N., & Huang, H.-C. (1999). Classes of nonseparable, spatio-temporal stationary covariance functions. Journal of the American Statistical Association, 94(448), 1330-1340.	Matheron, G. (1963). Principles of geostatistics. Economic Geology, 58(8), 1246-1266.
Alternatív nevek	spatiotemporal kriging, ST-kriging, space-time geostatistical interpolation, kriging in space-time	OK, kriging interpolation, geostatistical interpolation, BLUE spatial predictor
Kapcsolódó	4	4
Összefoglaló	Space-Time Kriging is a geostatistical interpolation method that predicts an unknown variable at any location and time by borrowing strength from nearby observations in both space and time simultaneously. It models the joint spatial-temporal covariance structure through a space-time variogram, then uses optimal linear weights to produce predictions with quantified uncertainty.	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.