विधियों की तुलना करें

	बायेसियन को-क्रीगिंग	को-क्रीगिंग: बहुभिन्नरूपी भूसांख्यिकीय अंतर्वेशन
क्षेत्र	स्थानिक विश्लेषण	स्थानिक विश्लेषण
परिवार	Regression model	Regression model
उद्भव वर्ष	1990s–2000s	1965-1978
प्रवर्तक	Gelfand, Banerjee & colleagues; building on Matheron's cokriging framework	Matheron, G.; extended by Journel & Huijbregts
प्रकार	Bayesian spatial interpolation	Geostatistical interpolation
मौलिक स्रोत	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
उपनाम	Bayesian cokriging, Bayesian co-regionalization, BCK, Bayesian multivariate kriging	cokriging, co-regionalization kriging, multivariate kriging, CK
संबंधित	5	5
सारांश	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.