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Bayesian Universal Kriging×Tavaline kriging×
ValdkondRuumianalüüsRuumianalüüs
PerekondRegression modelRegression model
Tekkeaasta1990s–2000s1963
LoojaDiggle, Tawn & Moyeed; Kitanidis; Handcock & SteinGeorges Matheron (formalising D.G. Krige's empirical work)
TüüpBayesian geostatistical interpolation with trendGeostatistical interpolation
AlgallikasDiggle, P. J., & Ribeiro, P. J. (2007). Model-Based Geostatistics. Springer. ISBN: 978-0387329079Matheron, G. (1963). Principles of geostatistics. Economic Geology, 58(8), 1246-1266. DOI ↗
RööpnimetusedBUK, Bayesian kriging with trend, Bayesian spatial interpolation with covariates, stochastic universal krigingOK, kriging interpolation, geostatistical interpolation, BLUE spatial predictor
Seotud64
KokkuvõteBayesian 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.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.
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ScholarGateVõrdle meetodeid: Bayesian Universal Kriging · Ordinary Kriging. Loetud 2026-06-18 aadressilt https://scholargate.app/et/compare