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ベイジアン・クリーギング(モデルベース地球統計学)×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1993–19981950
提唱者Diggle, Tawn & Moyeed; Handcock & SteinP. A. P. Moran (global measure, 1950); Roy Geary (Geary's C, 1954); Luc Anselin (LISA, 1995)
種類Bayesian spatial interpolationSpatial statistic / exploratory spatial data analysis
原典Diggle, P. J., Tawn, J. A., & Moyeed, R. A. (1998). Model-based geostatistics. Journal of the Royal Statistical Society: Series C (Applied Statistics), 47(3), 299–350. DOI ↗Moran, P. A. P. (1950). Notes on continuous stochastic phenomena. Biometrika, 37(1/2), 17–23. DOI ↗
別名Bayesian geostatistics, model-based geostatistics, Bayesian spatial interpolation, stochastic krigingspatial dependence, geographic autocorrelation, spatial clustering measure, SA
関連55
概要Bayesian Kriging embeds classical geostatistical interpolation inside a full probabilistic framework. Instead of treating variogram parameters as fixed point estimates, it places prior distributions on them and updates these priors with observed spatial data to obtain a posterior distribution. Predictions at unsampled locations are then marginalised over this uncertainty, yielding honest predictive intervals that account for both spatial dependence and parameter 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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ScholarGate手法を比較: Bayesian Kriging · Spatial Autocorrelation. 2026-06-17に以下より取得 https://scholargate.app/ja/compare