Sammenlign metoder

	Bayesiansk Geary's C	Bayesian Local Indicators of Spatial Association (Bayesian LISA)
Fagområde	Rumlig analyse	Rumlig analyse
Familie	Regression model	Regression model
Oprindelsesår	1954 (Bayesian framing: 2000s onward)	2000s–2010s
Ophavsperson	Geary (1954); Bayesian extension via hierarchical spatial modeling literature	Extension of Anselin (1995) LISA framework within Bayesian hierarchical modeling traditions (Banerjee, Carlin, Gelfand)
Type	Bayesian spatial autocorrelation statistic	Bayesian local spatial statistic
Oprindelig kilde	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.
Aliasser	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
Relaterede	6	6
Resumé	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.