方法对比

	贝叶斯通用克里金法	贝叶斯普通克里金
领域	空间分析	空间分析
方法族	Regression model	Regression model
起源年份	1990s–2000s	1993
提出者	Diggle, Tawn & Moyeed; Kitanidis; Handcock & Stein	Handcock & Stein (1993); Diggle & Ribeiro (2007)
类型	Bayesian geostatistical interpolation with trend	Bayesian geostatistical interpolation
开创性文献	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
别名	BUK, Bayesian kriging with trend, Bayesian spatial interpolation with covariates, stochastic universal kriging	Bayesian kriging, BOK, geostatistical Bayesian interpolation, Bayesian spatial prediction
相关	6	5
摘要	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.	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.