Comparar métodos
Revisa los métodos seleccionados uno junto a otro; las filas que difieren aparecen resaltadas.
| Global Getis-Ord Gi*× | Indicadores Locales de Asociación Espacial (LISA)× | |
|---|---|---|
| Campo | Análisis espacial | Análisis espacial |
| Familia | Regression model | Regression model |
| Año de origen≠ | 1992 | 1995 |
| Autor original≠ | Arthur Getis and J. Keith Ord | Luc Anselin |
| Tipo≠ | Global spatial clustering statistic | Local spatial statistic |
| Fuente seminal≠ | Getis, A., & Ord, J. K. (1992). The analysis of spatial association by use of distance statistics. Geographical Analysis, 24(3), 189-206. DOI ↗ | Anselin, L. (1995). Local Indicators of Spatial Association — LISA. Geographical Analysis, 27(2), 93–115. DOI ↗ |
| Alias | Global G statistic, Getis-Ord General G, General G*, Global spatial clustering statistic | LISA, local spatial autocorrelation statistics, local Moran's I, Anselin LISA |
| Relacionados≠ | 5 | 6 |
| Resumen≠ | The Global Getis-Ord Gi* statistic measures the overall degree of spatial clustering of high or low values across an entire study region. It answers whether the study area, taken as a whole, exhibits significant concentration of high values (hot clustering) or low values (cold clustering), returning a single summary Z-score for the entire dataset. | 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. |
| ScholarGateConjunto de datos ↗ |
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