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Bayesian Universal Kriging×Kriging Biasa Bayesian×
BidangAnalisis ReruangAnalisis Reruang
KeluargaRegression modelRegression model
Tahun asal1990s–2000s1993
PengasasDiggle, Tawn & Moyeed; Kitanidis; Handcock & SteinHandcock & Stein (1993); Diggle & Ribeiro (2007)
JenisBayesian geostatistical interpolation with trendBayesian geostatistical interpolation
Sumber perintisDiggle, P. J., & Ribeiro, P. J. (2007). Model-Based Geostatistics. Springer. ISBN: 978-0387329079Diggle, P. J., & Ribeiro, P. J. (2007). Model-Based Geostatistics. Springer. ISBN: 978-0387329079
AliasBUK, Bayesian kriging with trend, Bayesian spatial interpolation with covariates, stochastic universal krigingBayesian kriging, BOK, geostatistical Bayesian interpolation, Bayesian spatial prediction
Berkaitan65
RingkasanBayesian 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.
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ScholarGateBandingkan kaedah: Bayesian Universal Kriging · Bayesian Ordinary Kriging. Dicapai 2026-06-17 daripada https://scholargate.app/ms/compare