Comparar métodos

	Kriging Ordinario Bayesiano	Bayesian Co-Kriging
Campo	Análisis espacial	Análisis espacial
Familia	Regression model	Regression model
Año de origen	1993	1990s–2000s
Autor original	Handcock & Stein (1993); Diggle & Ribeiro (2007)	Gelfand, Banerjee & colleagues; building on Matheron's cokriging framework
Tipo	Bayesian geostatistical interpolation	Bayesian spatial interpolation
Fuente seminal	Diggle, P. J., & Ribeiro, P. J. (2007). Model-Based Geostatistics. Springer. ISBN: 978-0387329079	Diggle, P. J., & Ribeiro, P. J. (2007). Model-Based Geostatistics. Springer. ISBN: 978-0387329079
Alias	Bayesian kriging, BOK, geostatistical Bayesian interpolation, Bayesian spatial prediction	Bayesian cokriging, Bayesian co-regionalization, BCK, Bayesian multivariate kriging
Relacionados	5	5
Resumen	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 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.