Comparer des méthodes

	Co-Krigage Bayésien	Co-krigage : interpolation géostatistique multivariée
Domaine	Analyse spatiale	Analyse spatiale
Famille	Regression model	Regression model
Année d'origine	1990s–2000s	1965-1978
Auteur d'origine	Gelfand, Banerjee & colleagues; building on Matheron's cokriging framework	Matheron, G.; extended by Journel & Huijbregts
Type	Bayesian spatial interpolation	Geostatistical interpolation
Source fondatrice	Diggle, P. J., & Ribeiro, P. J. (2007). Model-Based Geostatistics. Springer. ISBN: 978-0387329079	Journel, A. G., & Huijbregts, C. J. (1978). Mining Geostatistics. Academic Press, London. ISBN: 978-0123910561
Alias	Bayesian cokriging, Bayesian co-regionalization, BCK, Bayesian multivariate kriging	cokriging, co-regionalization kriging, multivariate kriging, CK
Apparentées	5	5
Résumé	Bayesian Co-Kriging is a multivariate geostatistical method that uses auxiliary spatially correlated variables to improve predictions of a primary variable of interest. By placing Bayesian priors on cross-covariance parameters, it propagates all uncertainty — including parameter uncertainty — into the prediction intervals, yielding fully probabilistic maps with calibrated uncertainty bounds.	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.