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Bayesian Local Indicators of Spatial Association (Bayesian LISA)×LISA (Local Indicators of Spatial Association)×
PodručjeProstorna analizaProstorna analiza
ObiteljRegression modelRegression model
Godina nastanka2000s–2010s1995
TvoracExtension of Anselin (1995) LISA framework within Bayesian hierarchical modeling traditions (Banerjee, Carlin, Gelfand)Luc Anselin
VrstaBayesian local spatial statisticLocal spatial statistic
Temeljni izvorAnselin, L. (1995). Local indicators of spatial association—LISA. Geographical Analysis, 27(2), 93–115. DOI ↗Anselin, L. (1995). Local Indicators of Spatial Association — LISA. Geographical Analysis, 27(2), 93–115. DOI ↗
Drugi naziviBayesian LISA, Bayesian local spatial autocorrelation, Bayesian local Moran, B-LISALISA, local spatial autocorrelation statistics, local Moran's I, Anselin LISA
Srodne66
SažetakBayesian 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.
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ScholarGateUsporedite metode: Bayesian Local Indicators of Spatial Association · Local Indicators of Spatial Association. Preuzeto 2026-06-20 s https://scholargate.app/hr/compare