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	Krigaggio Universale Bayesiano	Co-kriging: Interpolazione Geostatistica Multivariata
Campo	Analisi spaziale	Analisi spaziale
Famiglia	Regression model	Regression model
Anno di origine	1990s–2000s	1965-1978
Ideatore	Diggle, Tawn & Moyeed; Kitanidis; Handcock & Stein	Matheron, G.; extended by Journel & Huijbregts
Tipo	Bayesian geostatistical interpolation with trend	Geostatistical interpolation
Fonte seminale	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	BUK, Bayesian kriging with trend, Bayesian spatial interpolation with covariates, stochastic universal kriging	cokriging, co-regionalization kriging, multivariate kriging, CK
Correlati	6	5
Sintesi	Bayesian Universal Kriging (BUK) extends classical universal kriging by placing prior distributions on trend coefficients and spatial covariance parameters, then propagating full posterior uncertainty into predictions. It interpolates spatially referenced continuous data while simultaneously estimating large-scale deterministic trends driven by covariates and small-scale stochastic spatial dependence, yielding prediction intervals that honestly account for both parameter and interpolation uncertainty.	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.