Comparar métodos

	Bayesian Geary's C	Indicadores Bayesianos Locais de Associação Espacial (Bayesian LISA)
Área	Análise espacial	Análise espacial
Família	Regression model	Regression model
Ano de origem	1954 (Bayesian framing: 2000s onward)	2000s–2010s
Autor original	Geary (1954); Bayesian extension via hierarchical spatial modeling literature	Extension of Anselin (1995) LISA framework within Bayesian hierarchical modeling traditions (Banerjee, Carlin, Gelfand)
Tipo	Bayesian spatial autocorrelation statistic	Bayesian local spatial statistic
Fonte seminal	Geary, R. C. (1954). The contiguity ratio and statistical mapping. The Incorporated Statistician, 5(3), 115–145.	Anselin, L. (1995). Local indicators of spatial association—LISA. Geographical Analysis, 27(2), 93–115.
Outros nomes	Bayesian Geary C, Bayesian spatial contiguity statistic, Geary's C (Bayesian), Bayesian contiguity ratio	Bayesian LISA, Bayesian local spatial autocorrelation, Bayesian local Moran, B-LISA
Relacionados	6	6
Resumo	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 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.