Compară metode

	Kriging global	Co-kriging: Interpolare Geostatistică Multivariată
Domeniu	Analiză spațială	Analiză spațială
Familie	Regression model	Regression model
Anul apariției	1960s–1993	1965-1978
Autorul original	Georges Matheron (kriging framework); global neighborhood usage formalized in applied geostatistics	Matheron, G.; extended by Journel & Huijbregts
Tip	Geostatistical interpolation	Geostatistical interpolation
Sursa seminală	Cressie, N. A. C. (1993). Statistics for Spatial Data (revised ed.). Wiley-Interscience. ISBN: 978-0471002550	Journel, A. G., & Huijbregts, C. J. (1978). Mining Geostatistics. Academic Press, London. ISBN: 978-0123910561
Denumiri alternative	global-neighborhood kriging, full-data kriging, exhaustive kriging, non-local kriging	cokriging, co-regionalization kriging, multivariate kriging, CK
Înrudite	5	5
Rezumat	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.	Co-kriging is a geostatistical interpolation technique that predicts the spatial distribution of a primary variable by leveraging its spatial cross-correlation with one or more secondary (co-) variables. It extends ordinary kriging to multivariate settings, yielding more accurate predictions when the secondary variable is more densely sampled or spatially correlated with the primary variable of interest.