Comparar métodos
Revisa los métodos seleccionados uno junto a otro; las filas que difieren aparecen resaltadas.
| Modelo de Error Espacial Global (SEM)× | Índice I de Moran× | |
|---|---|---|
| Campo | Análisis espacial | Análisis espacial |
| Familia | Regression model | Regression model |
| Año de origen≠ | 1988 | 1950 |
| Autor original≠ | Luc Anselin | Patrick A. P. Moran |
| Tipo≠ | Spatial regression model | Spatial autocorrelation statistic |
| Fuente seminal≠ | Anselin, L. (1988). Spatial Econometrics: Methods and Models. Kluwer Academic Publishers. ISBN: 978-9024737322 | Moran, P. A. P. (1950). Notes on continuous stochastic phenomena. Biometrika, 37(1/2), 17–23. DOI ↗ |
| Alias | SEM, spatial error model, spatial error regression, global SEM | Moran's I statistic, global Moran's I, spatial autocorrelation index, Moran index |
| Relacionados≠ | 5 | 6 |
| Resumen≠ | The Global Spatial Error Model (SEM) is a spatial regression technique that accounts for spatially autocorrelated error terms using a single, globally constant spatial parameter. It separates genuine predictor effects from spatial nuisance dependence in the residuals, yielding unbiased and efficient coefficient estimates when spatial error correlation is present across all observations. | Moran's I is the standard global statistic for detecting spatial autocorrelation: whether nearby locations tend to share similar values. The index ranges from approximately −1 (perfect dispersion) through 0 (spatial randomness) to +1 (perfect clustering), allowing researchers to test whether a geographic pattern differs from complete spatial randomness with a single, interpretable number. |
| ScholarGateConjunto de datos ↗ |
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