Compară metode

	Cokriging	Crinaj universal (Crinaj cu tendință)
Domeniu	Analiză spațială	Analiză spațială
Familie	Regression model	Regression model
Anul apariției	1963	1969
Autorul original	Georges Matheron (geostatistics); multivariate extension	Georges Matheron
Tip	Multivariate geostatistical interpolation	Geostatistical interpolation with spatial trend
Sursa seminală	Matheron, G. (1963). Principles of geostatistics. Economic Geology, 58(8), 1246–1266.	Matheron, G. (1963). Principles of geostatistics. Economic Geology, 58(8), 1246–1266.
Denumiri alternative	co-kriging, multivariate kriging, ortak kriging	kriging with a trend, kriging with drift, trend kriging, evrensel kriging
Înrudite	3	3
Rezumat	Cokriging extends kriging to use one or more correlated secondary variables to improve prediction of a primary variable. When the variable of interest is sparsely sampled but a related, cheaper-to-measure variable is densely sampled, cokriging borrows strength from the secondary variable through their cross-correlation, yielding more accurate interpolations and prediction variances than kriging the primary variable alone.	Universal kriging generalizes ordinary kriging to data whose mean varies systematically across space — a spatial trend or 'drift'. It models the mean as a function of the coordinates (or covariates) and krigs the residuals, so it can interpolate variables that drift in a preferred direction, such as temperature falling with latitude or a pollutant gradient, while still returning prediction variances.