Comparer des méthodes

	Bayesian Geary's C	Autocorrélation spatiale bayésienne
Domaine	Analyse spatiale	Analyse spatiale
Famille	Regression model	Regression model
Année d'origine	1954 (Bayesian framing: 2000s onward)	1991
Auteur d'origine	Geary (1954); Bayesian extension via hierarchical spatial modeling literature	Besag, York & Mollie
Type	Bayesian spatial autocorrelation statistic	Bayesian hierarchical spatial model
Source fondatrice	Geary, R. C. (1954). The contiguity ratio and statistical mapping. The Incorporated Statistician, 5(3), 115–145.	Besag, 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.
Alias	Bayesian Geary C, Bayesian spatial contiguity statistic, Geary's C (Bayesian), Bayesian contiguity ratio	Bayesian spatial dependence, Bayesian LISA, Bayesian spatial clustering, BSA
Apparentées	6	6
Résumé	Bayesian Geary's C embeds the classical Geary contiguity ratio within a Bayesian hierarchical framework. Instead of a single point estimate and asymptotic p-value, it produces a posterior distribution over the statistic (or over spatially structured random effects), quantifying uncertainty about spatial autocorrelation while formally incorporating prior knowledge about the spatial process.	Bayesian 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.