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| Đồng-Kriging Bayes× | Bayesian Universal Kriging× | |
|---|---|---|
| Lĩnh vực | Phân tích không gian | Phân tích không gian |
| Họ | Regression model | Regression model |
| Năm ra đời | 1990s–2000s | 1990s–2000s |
| Người khởi xướng≠ | Gelfand, Banerjee & colleagues; building on Matheron's cokriging framework | Diggle, Tawn & Moyeed; Kitanidis; Handcock & Stein |
| Loại≠ | Bayesian spatial interpolation | Bayesian geostatistical interpolation with trend |
| Công trình gốc | 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 |
| Tên gọi khác | Bayesian cokriging, Bayesian co-regionalization, BCK, Bayesian multivariate kriging | BUK, Bayesian kriging with trend, Bayesian spatial interpolation with covariates, stochastic universal kriging |
| Liên quan≠ | 5 | 6 |
| Tóm tắt≠ | Bayesian Co-Kriging is a multivariate geostatistical method that uses auxiliary spatially correlated variables to improve predictions of a primary variable of interest. By placing Bayesian priors on cross-covariance parameters, it propagates all uncertainty — including parameter uncertainty — into the prediction intervals, yielding fully probabilistic maps with calibrated uncertainty bounds. | 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. |
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