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Autocorrélation spatiale bayésienne×Autocorrélation spatiale locale×
DomaineAnalyse spatialeAnalyse spatiale
FamilleRegression modelRegression model
Année d'origine19911995
Auteur d'origineBesag, York & MollieLuc Anselin
TypeBayesian hierarchical spatial modelSpatial association analysis
Source fondatriceBesag, J., York, J., & Mollie, A. (1991). Bayesian image restoration, with two applications in spatial statistics. Annals of the Institute of Statistical Mathematics, 43(1), 1–20. DOI ↗Anselin, L. (1995). Local indicators of spatial association — LISA. Geographical Analysis, 27(2), 93–115. DOI ↗
AliasBayesian spatial dependence, Bayesian LISA, Bayesian spatial clustering, BSAlocal spatial association, local SA, LISA methods, local spatial clustering
Apparentées66
RésuméBayesian Spatial Autocorrelation embeds spatial dependence directly into a Bayesian hierarchical model. A Conditional Autoregressive (CAR) prior encodes the expectation that neighboring areas are more similar than distant ones, and posterior inference is obtained via MCMC. This approach is especially valuable in disease mapping, ecology, and regional science, where small-area estimates need borrowing strength across neighbors.Local Spatial Autocorrelation methods decompose global spatial clustering into location-specific statistics, revealing where in a study area significant clustering or dispersion occurs. Each observation receives its own association score and significance value, enabling the detection of spatial hot spots, cold spots, and spatial outliers rather than reporting a single summary statistic.
ScholarGateJeu de données
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ScholarGateComparer des méthodes: Bayesian Spatial Autocorrelation · Local Spatial Autocorrelation. Consulté le 2026-06-17 sur https://scholargate.app/fr/compare