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Bayesovské lokálne indikátory priestorovej asociácie (Bayesian LISA)×Priestorová autokorelácia×
OdborPriestorová analýzaPriestorová analýza
RodinaRegression modelRegression model
Rok vzniku2000s–2010s1950
TvorcaExtension of Anselin (1995) LISA framework within Bayesian hierarchical modeling traditions (Banerjee, Carlin, Gelfand)P. A. P. Moran (global measure, 1950); Roy Geary (Geary's C, 1954); Luc Anselin (LISA, 1995)
TypBayesian local spatial statisticSpatial statistic / exploratory spatial data analysis
Pôvodný zdrojAnselin, L. (1995). Local indicators of spatial association—LISA. Geographical Analysis, 27(2), 93–115. DOI ↗Moran, P. A. P. (1950). Notes on continuous stochastic phenomena. Biometrika, 37(1/2), 17–23. DOI ↗
Ďalšie názvyBayesian LISA, Bayesian local spatial autocorrelation, Bayesian local Moran, B-LISAspatial dependence, geographic autocorrelation, spatial clustering measure, SA
Príbuzné65
ZhrnutieBayesian Local Indicators of Spatial Association extend the classical LISA framework by embedding local spatial association statistics within a Bayesian hierarchical model. Rather than relying on asymptotic permutation-based significance tests, this approach places prior distributions on spatial parameters and derives posterior probabilities that a location is part of a genuine spatial cluster, accounting for uncertainty and borrowing strength across nearby units.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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ScholarGatePorovnať metódy: Bayesian Local Indicators of Spatial Association · Spatial Autocorrelation. Získané 2026-06-19 z https://scholargate.app/sk/compare