Salīdzināt metodes

	Beiešiskais Morana I	Lokālais Morana I (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 autocorrelation 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	Local Indicator of Spatial Association, LISA statistic, Anselin Local Moran, local spatial autocorrelation index
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.	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.