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분야공간분석공간분석
계열Regression modelRegression model
기원 연도1990s–2000s1969
창시자Diggle, Tawn & Moyeed; Kitanidis; Handcock & SteinGeorges Matheron
유형Bayesian geostatistical interpolation with trendGeostatistical interpolation with spatial trend
원전Diggle, P. J., & Ribeiro, P. J. (2007). Model-Based Geostatistics. Springer. ISBN: 978-0387329079Matheron, G. (1963). Principles of geostatistics. Economic Geology, 58(8), 1246–1266. DOI ↗
별칭BUK, Bayesian kriging with trend, Bayesian spatial interpolation with covariates, stochastic universal krigingkriging with a trend, kriging with drift, trend kriging, evrensel kriging
관련63
요약Bayesian 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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