Methoden vergleichen

	Bayesian Local Indicators of Spatial Association (Bayesian LISA)	Lokales Geary's C
Fachgebiet	Räumliche Analyse	Räumliche Analyse
Familie	Regression model	Regression model
Entstehungsjahr	2000s–2010s	1995
Urheber	Extension of Anselin (1995) LISA framework within Bayesian hierarchical modeling traditions (Banerjee, Carlin, Gelfand)	Luc Anselin
Typ	Bayesian local spatial statistic	Local spatial statistic
Wegweisende Quelle	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.
Aliasnamen	Bayesian LISA, Bayesian local spatial autocorrelation, Bayesian local Moran, B-LISA	Local Geary, local spatial contiguity ratio, LISA Geary, local c statistic
Verwandt	6	6
Zusammenfassung	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.	Local Geary's C is a local indicator of spatial association (LISA) that measures, for each location, how dissimilar its value is from its immediate neighbours. Unlike Local Moran's I, which detects clustering of similar values, Local Geary's C focuses on squared value differences and is especially sensitive to local spatial outliers and local heterogeneity.