Сравнение методов

	Байесовский универсальный кригинг	Универсальный кригинг (кригинг с трендом)
Область	Пространственный анализ	Пространственный анализ
Семейство	Regression model	Regression model
Год появления	1990s–2000s	1969
Автор метода	Diggle, Tawn & Moyeed; Kitanidis; Handcock & Stein	Georges Matheron
Тип	Bayesian geostatistical interpolation with trend	Geostatistical interpolation with spatial trend
Основополагающий источник	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.
Другие названия	BUK, Bayesian kriging with trend, Bayesian spatial interpolation with covariates, stochastic universal kriging	kriging with a trend, kriging with drift, trend kriging, evrensel kriging
Связанные	6	3
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.	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.