Comparer des méthodes

	Indicateurs locaux bayésiens d'association spatiale (Bayesian LISA)	Indicateurs Locaux d'Association Spatiale (LISA)
Domaine	Analyse spatiale	Analyse spatiale
Famille	Regression model	Regression model
Année d'origine	2000s–2010s	1995
Auteur d'origine	Extension of Anselin (1995) LISA framework within Bayesian hierarchical modeling traditions (Banerjee, Carlin, Gelfand)	Luc Anselin
Type	Bayesian local spatial statistic	Local spatial statistic
Source fondatrice	Anselin, L. (1995). Local indicators of spatial association—LISA. Geographical Analysis, 27(2), 93–115.	Anselin, L. (1995). Local Indicators of Spatial Association — LISA. Geographical Analysis, 27(2), 93–115.
Alias	Bayesian LISA, Bayesian local spatial autocorrelation, Bayesian local Moran, B-LISA	LISA, local spatial autocorrelation statistics, local Moran's I, Anselin LISA
Apparentées	6	6
Résumé	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.	LISA, introduced by Luc Anselin in 1995, decomposes a global spatial autocorrelation index into a location-specific statistic for every observation. It identifies where statistically significant spatial clusters and outliers occur on a map, enabling researchers to move beyond a single global summary and pinpoint the geographic sources of spatial dependence.