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Bayesovské obyčejné krigování×Prostorová autokorelace×
OborProstorová analýzaProstorová analýza
RodinaRegression modelRegression model
Rok vzniku19931950
TvůrceHandcock & Stein (1993); Diggle & Ribeiro (2007)P. A. P. Moran (global measure, 1950); Roy Geary (Geary's C, 1954); Luc Anselin (LISA, 1995)
TypBayesian geostatistical interpolationSpatial statistic / exploratory spatial data analysis
Původní zdrojDiggle, 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 ↗
Další názvyBayesian kriging, BOK, geostatistical Bayesian interpolation, Bayesian spatial predictionspatial dependence, geographic autocorrelation, spatial clustering measure, SA
Příbuzné55
ShrnutíBayesian 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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ScholarGatePorovnat metody: Bayesian Ordinary Kriging · Spatial Autocorrelation. Získáno 2026-06-17 z https://scholargate.app/cs/compare