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| Kriging Universal Bayesiana× | Kriging Universal (Kriging amb Tendència)× | |
|---|---|---|
| Camp | Anàlisi espacial | Anàlisi espacial |
| Família | Regression model | Regression model |
| Any d'origen≠ | 1990s–2000s | 1969 |
| Autor original≠ | Diggle, Tawn & Moyeed; Kitanidis; Handcock & Stein | Georges Matheron |
| Tipus≠ | Bayesian geostatistical interpolation with trend | Geostatistical interpolation with spatial trend |
| Font seminal≠ | 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. DOI ↗ |
| Àlies | BUK, Bayesian kriging with trend, Bayesian spatial interpolation with covariates, stochastic universal kriging | kriging with a trend, kriging with drift, trend kriging, evrensel kriging |
| Relacionats≠ | 6 | 3 |
| Resum≠ | 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. | Universal kriging generalizes ordinary kriging to data whose mean varies systematically across space — a spatial trend or 'drift'. It models the mean as a function of the coordinates (or covariates) and krigs the residuals, so it can interpolate variables that drift in a preferred direction, such as temperature falling with latitude or a pollutant gradient, while still returning prediction variances. |
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