Сравнение методов

	Байесовский универсальный кригинг	Байесовский обычный кригинг
Область	Пространственный анализ	Пространственный анализ
Семейство	Regression model	Regression model
Год появления	1990s–2000s	1993
Автор метода	Diggle, Tawn & Moyeed; Kitanidis; Handcock & Stein	Handcock & Stein (1993); Diggle & Ribeiro (2007)
Тип	Bayesian geostatistical interpolation with trend	Bayesian geostatistical interpolation
Основополагающий источник	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
Другие названия	BUK, Bayesian kriging with trend, Bayesian spatial interpolation with covariates, stochastic universal kriging	Bayesian kriging, BOK, geostatistical Bayesian interpolation, Bayesian spatial prediction
Связанные	6	5
Сводка	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.	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.