Comparar métodos
Revisa los métodos seleccionados uno junto a otro; las filas que difieren aparecen resaltadas.
| Modelo Bayesiano de Error Espacial× | Índice I de Moran× | |
|---|---|---|
| Campo | Análisis espacial | Análisis espacial |
| Familia | Regression model | Regression model |
| Año de origen≠ | 1988 (classical SEM); 2009 (Bayesian formulation) | 1950 |
| Autor original≠ | LeSage & Pace (Bayesian treatment); Anselin (classical SEM) | Patrick A. P. Moran |
| Tipo≠ | Bayesian spatial regression | Spatial autocorrelation statistic |
| Fuente seminal≠ | LeSage, J. P., & Pace, R. K. (2009). Introduction to Spatial Econometrics. CRC Press / Taylor & Francis. ISBN: 978-1420064247 | Moran, P. A. P. (1950). Notes on continuous stochastic phenomena. Biometrika, 37(1/2), 17–23. DOI ↗ |
| Alias | Bayesian SEM, Bayesian spatial-error regression, BSEM spatial econometrics, Bayesian spatially correlated error model | Moran's I statistic, global Moran's I, spatial autocorrelation index, Moran index |
| Relacionados | 6 | 6 |
| Resumen≠ | The Bayesian Spatial Error Model (Bayesian SEM) estimates a regression in which spatially correlated disturbances are explicitly modelled through a spatial weights matrix, while all parameters — regression coefficients, spatial error autocorrelation, and error variance — receive full posterior distributions via Bayesian inference rather than point estimates. | 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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