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Bayesian Universal Kriging×Co-kriging: Interpolasi Geostatistik Multivariat×
BidangAnalisis ReruangAnalisis Reruang
KeluargaRegression modelRegression model
Tahun asal1990s–2000s1965-1978
PengasasDiggle, Tawn & Moyeed; Kitanidis; Handcock & SteinMatheron, G.; extended by Journel & Huijbregts
JenisBayesian geostatistical interpolation with trendGeostatistical interpolation
Sumber perintisDiggle, P. J., & Ribeiro, P. J. (2007). Model-Based Geostatistics. Springer. ISBN: 978-0387329079Journel, A. G., & Huijbregts, C. J. (1978). Mining Geostatistics. Academic Press, London. ISBN: 978-0123910561
AliasBUK, Bayesian kriging with trend, Bayesian spatial interpolation with covariates, stochastic universal krigingcokriging, co-regionalization kriging, multivariate kriging, CK
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.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.
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ScholarGateBandingkan kaedah: Bayesian Universal Kriging · Co-kriging. Dicapai 2026-06-17 daripada https://scholargate.app/ms/compare