Salīdzināt metodes

	Beiešiskais Morana I	Lokālās telpiskās asociācijas indikatori (LISA)
Nozare	Telpiskā analīze	Telpiskā analīze
Saime	Regression model	Regression model
Izcelsmes gads	1950 / 2000s	1995
Autors	Moran (1950), Bayesian extension developed in spatial statistics literature (late 1990s–2000s)	Luc Anselin
Tips	Bayesian spatial autocorrelation test	Local spatial statistic
Pirmavots	Haining, R. (2003). Spatial Data Analysis: Theory and Practice. Cambridge University Press. ISBN: 9780521774611	Anselin, L. (1995). Local Indicators of Spatial Association — LISA. Geographical Analysis, 27(2), 93–115.
Citi nosaukumi	Bayesian spatial autocorrelation test, Bayesian Moran statistic, Moran's I under Bayesian inference, Bayesian global spatial association	LISA, local spatial autocorrelation statistics, local Moran's I, Anselin LISA
Saistītās	6	6
Kopsavilkums	Bayesian Moran's I embeds the classical Moran's I spatial autocorrelation test within a Bayesian probabilistic framework. Rather than producing a single p-value, it yields a posterior distribution over the spatial autocorrelation parameter, enabling uncertainty quantification, incorporation of prior knowledge, and more principled inference in small or irregular spatial datasets.	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.