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ベイズ汎用クリギング×空間的自己相関×
分野空間分析空間分析
系統Regression modelRegression model
提唱年1990s–2000s1950
提唱者Diggle, Tawn & Moyeed; Kitanidis; Handcock & SteinP. A. P. Moran (global measure, 1950); Roy Geary (Geary's C, 1954); Luc Anselin (LISA, 1995)
種類Bayesian geostatistical interpolation with trendSpatial statistic / exploratory spatial data analysis
原典Diggle, P. J., & Ribeiro, P. J. (2007). Model-Based Geostatistics. Springer. ISBN: 978-0387329079Moran, P. A. P. (1950). Notes on continuous stochastic phenomena. Biometrika, 37(1/2), 17–23. DOI ↗
別名BUK, Bayesian kriging with trend, Bayesian spatial interpolation with covariates, stochastic universal krigingspatial dependence, geographic autocorrelation, spatial clustering measure, SA
関連65
概要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.Spatial autocorrelation quantifies the degree to which a variable's values at nearby locations resemble each other more (positive autocorrelation) or less (negative autocorrelation) than expected by chance. Global indices such as Moran's I summarise the pattern across the entire study area, while local variants reveal clusters and outliers at the level of individual observations.
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  3. PUBLISHED

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ScholarGate手法を比較: Bayesian Universal Kriging · Spatial Autocorrelation. 2026-06-17に以下より取得 https://scholargate.app/ja/compare