Regression modelGIS / spatial
Local Moran's I (LISA)
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.
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Sources
- Anselin, L. (1995). Local indicators of spatial association—LISA. Geographical Analysis, 27(2), 93–115. DOI: 10.1111/j.1538-4632.1995.tb00338.x ↗
- Anselin, L. (2010). Local spatial autocorrelation. In A. S. Fotheringham & P. A. Rogerson (Eds.), The SAGE Handbook of Spatial Analysis (pp. 255–278). SAGE Publications. link ↗
Related methods
Referenced by
Bayesian Local Indicators of Spatial AssociationBayesian Moran's IGetis-Ord Gi*Global Moran's IGlobal Spatial AutocorrelationHot Spot AnalysisLocal Geary's CLocal Getis-Ord Gi*Local Hot Spot AnalysisLocal Kernel Density EstimationLocal Spatial AutocorrelationMoran's IMultiscale Getis-Ord Gi*Multiscale Moran's IPanel Local Indicators of Spatial AssociationRobust Getis-Ord Gi*Robust Local Indicators of Spatial AssociationRobust Moran's ISpace-Time Local Indicators of Spatial AssociationSpace-Time Moran's ISpace-Time Spatial Autocorrelation