Salīdzināt metodes

	Globālā telpiskā autokorelācija	Telpiskā autokorelācija
Nozare	Telpiskā analīze	Telpiskā analīze
Saime	Regression model	Regression model
Izcelsmes gads	1950	1950
Autors	P. A. P. Moran (Moran's I, 1950); generalized by Luc Anselin	P. A. P. Moran (global measure, 1950); Roy Geary (Geary's C, 1954); Luc Anselin (LISA, 1995)
Tips	Spatial statistic / hypothesis test	Spatial statistic / exploratory spatial data analysis
Pirmavots	Moran, P. A. P. (1950). Notes on continuous stochastic phenomena. Biometrika, 37(1/2), 17–23.	Moran, P. A. P. (1950). Notes on continuous stochastic phenomena. Biometrika, 37(1/2), 17–23.
Citi nosaukumi	global spatial dependence, global Moran's I, GSA, global spatial clustering measure	spatial dependence, geographic autocorrelation, spatial clustering measure, SA
Saistītās	6	5
Kopsavilkums	Global Spatial Autocorrelation measures the degree to which similar values cluster together across an entire study area. Rather than identifying where clusters occur, it yields a single summary statistic — most commonly Moran's I — that quantifies whether spatial proximity coincides with value similarity, dissimilarity, or randomness across all observations simultaneously.	Spatial autocorrelation quantifies the degree to which a variable's values at nearby locations resemble each other more (positive autocorrelation) or less (negative autocorrelation) than expected by chance. Global indices such as Moran's I summarise the pattern across the entire study area, while local variants reveal clusters and outliers at the level of individual observations.