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الكراجينغ العادي البيزي×الارتباط التلقائي المكاني×
المجالالتحليل المكانيالتحليل المكاني
العائلةRegression modelRegression model
سنة النشأة19931950
صاحب الطريقةHandcock & Stein (1993); Diggle & Ribeiro (2007)P. A. P. Moran (global measure, 1950); Roy Geary (Geary's C, 1954); Luc Anselin (LISA, 1995)
النوعBayesian geostatistical interpolationSpatial statistic / exploratory spatial data analysis
المصدر التأسيسيDiggle, 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 ↗
الأسماء البديلةBayesian kriging, BOK, geostatistical Bayesian interpolation, Bayesian spatial predictionspatial dependence, geographic autocorrelation, spatial clustering measure, SA
ذات صلة55
الملخصBayesian 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.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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ScholarGateقارن الطرق: Bayesian Ordinary Kriging · Spatial Autocorrelation. استُرجع بتاريخ 2026-06-17 من https://scholargate.app/ar/compare