विधियों की तुलना करें

	Bayesian Local Indicators of Spatial Association (Bayesian LISA)	स्थानीय मोरान का I (LISA)
क्षेत्र	स्थानिक विश्लेषण	स्थानिक विश्लेषण
परिवार	Regression model	Regression model
उद्भव वर्ष	2000s–2010s	1995
प्रवर्तक	Extension of Anselin (1995) LISA framework within Bayesian hierarchical modeling traditions (Banerjee, Carlin, Gelfand)	Luc Anselin
प्रकार	Bayesian local spatial statistic	Local spatial autocorrelation statistic
मौलिक स्रोत	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.
उपनाम	Bayesian LISA, Bayesian local spatial autocorrelation, Bayesian local Moran, B-LISA	Local Indicator of Spatial Association, LISA statistic, Anselin Local Moran, local spatial autocorrelation index
संबंधित	6	6
सारांश	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 Moran's I, introduced by Luc Anselin in 1995, is a Local Indicator of Spatial Association (LISA) that decomposes global spatial autocorrelation into location-specific contributions. For every observation it produces a signed statistic and a significance value, enabling researchers to identify spatial clusters (high-high, low-low) and spatial outliers (high-low, low-high) on a map.