Comparar métodos
Revisa los métodos seleccionados uno junto a otro; las filas que difieren aparecen resaltadas.
| Modelo de Retardo Espacial Local× | Autocorrelación espacial× | |
|---|---|---|
| Campo | Análisis espacial | Análisis espacial |
| Familia | Regression model | Regression model |
| Año de origen≠ | 1988 (global); 2000s (local extensions) | 1950 |
| Autor original≠ | Anselin (global SLM, 1988); local extension via Fotheringham, Brunsdon & Charlton (GWR framework, 2002) | P. A. P. Moran (global measure, 1950); Roy Geary (Geary's C, 1954); Luc Anselin (LISA, 1995) |
| Tipo≠ | Spatially varying regression model | Spatial statistic / exploratory spatial data analysis |
| Fuente seminal≠ | Anselin, L. (1988). Spatial Econometrics: Methods and Models. Kluwer Academic Publishers. ISBN: 978-9024737215 | Moran, P. A. P. (1950). Notes on continuous stochastic phenomena. Biometrika, 37(1/2), 17–23. DOI ↗ |
| Alias | local SLM, geographically weighted spatial lag model, GW-SLM, spatially varying lag model | spatial dependence, geographic autocorrelation, spatial clustering measure, SA |
| Relacionados | 5 | 5 |
| Resumen≠ | The Local Spatial Lag Model extends the classical spatial lag model by allowing both the spatial autocorrelation parameter and the regression coefficients to vary across geographic locations. Instead of one global estimate of how neighboring outcomes influence each observation, the model fits location-specific parameters using kernel-weighted local estimation, revealing spatial heterogeneity in spatial dependence. | 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. |
| ScholarGateConjunto de datos ↗ |
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