Confronta i metodi

	Bayesian Ordinary Kriging	Kriging Bayesiano (Geostatistica basata su modello)
Campo	Analisi spaziale	Analisi spaziale
Famiglia	Regression model	Regression model
Anno di origine	1993	1993–1998
Ideatore	Handcock & Stein (1993); Diggle & Ribeiro (2007)	Diggle, Tawn & Moyeed; Handcock & Stein
Tipo	Bayesian geostatistical interpolation	Bayesian spatial interpolation
Fonte seminale	Diggle, P. J., & Ribeiro, P. J. (2007). Model-Based Geostatistics. Springer. ISBN: 978-0387329079	Diggle, P. J., Tawn, J. A., & Moyeed, R. A. (1998). Model-based geostatistics. Journal of the Royal Statistical Society: Series C (Applied Statistics), 47(3), 299–350.
Alias	Bayesian kriging, BOK, geostatistical Bayesian interpolation, Bayesian spatial prediction	Bayesian geostatistics, model-based geostatistics, Bayesian spatial interpolation, stochastic kriging
Correlati	5	5
Sintesi	Bayesian Ordinary Kriging is a geostatistical interpolation method that combines classical ordinary kriging with a Bayesian framework to jointly estimate the spatial covariance parameters and produce predictions at unsampled locations. Unlike plug-in kriging, it propagates uncertainty about variogram parameters through to the predictive distribution, yielding more honest uncertainty quantification.	Bayesian Kriging embeds classical geostatistical interpolation inside a full probabilistic framework. Instead of treating variogram parameters as fixed point estimates, it places prior distributions on them and updates these priors with observed spatial data to obtain a posterior distribution. Predictions at unsampled locations are then marginalised over this uncertainty, yielding honest predictive intervals that account for both spatial dependence and parameter uncertainty.