Comparer des méthodes

	Moran's I multiscalaire	Autocorrélation spatiale
Domaine	Analyse spatiale	Analyse spatiale
Famille	Regression model	Regression model
Année d'origine	1950 (base); multiscale variant 1980s-1990s	1950
Auteur d'origine	P. A. P. Moran (base statistic, 1950); multiscale extension developed through spatial ecology and geography literature	P. A. P. Moran (global measure, 1950); Roy Geary (Geary's C, 1954); Luc Anselin (LISA, 1995)
Type	Spatial autocorrelation statistic	Spatial statistic / exploratory spatial data analysis
Source fondatrice	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.
Alias	multi-scale Moran's I, spatial correlogram Moran, Moran correlogram, multiscale spatial autocorrelation	spatial dependence, geographic autocorrelation, spatial clustering measure, SA
Apparentées	6	5
Résumé	Multiscale Moran's I extends the classic global Moran's I statistic by computing spatial autocorrelation across a series of distance lags or spatial scales. The resulting spatial correlogram reveals at which geographic scales clusters or dispersions of a variable exist, offering richer insight than a single summary statistic.	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.