Methoden vergleichen

	Bayesian Ordinary Kriging	Ordinary Kriging
Fachgebiet	Räumliche Analyse	Räumliche Analyse
Familie	Regression model	Regression model
Entstehungsjahr	1993	1963
Urheber	Handcock & Stein (1993); Diggle & Ribeiro (2007)	Georges Matheron (formalising D.G. Krige's empirical work)
Typ	Bayesian geostatistical interpolation	Geostatistical interpolation
Wegweisende Quelle	Diggle, P. J., & Ribeiro, P. J. (2007). Model-Based Geostatistics. Springer. ISBN: 978-0387329079	Matheron, G. (1963). Principles of geostatistics. Economic Geology, 58(8), 1246-1266.
Aliasnamen	Bayesian kriging, BOK, geostatistical Bayesian interpolation, Bayesian spatial prediction	OK, kriging interpolation, geostatistical interpolation, BLUE spatial predictor
Verwandt	5	4
Zusammenfassung	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.	Ordinary Kriging (OK) is the standard geostatistical method for interpolating a continuous spatial variable at unsampled locations. It derives optimal, unbiased weights from the spatial covariance structure of the data, making it the Best Linear Unbiased Predictor (BLUP) under stationarity assumptions. Unlike simpler distance-based methods, it also provides a prediction uncertainty (kriging variance) at every interpolated point.