Comparar métodos
Examine os métodos selecionados lado a lado; as linhas que diferem ficam destacadas.
| Modelo de Durbin Espacial Local× | Regressão Espacial Local× | |
|---|---|---|
| Área | Análise espacial | Análise espacial |
| Família | Regression model | Regression model |
| Ano de origem≠ | 2002–2009 | 1996 |
| Autor original≠ | LeSage & Pace (SDM foundation); local adaptation via Fotheringham et al. GWR framework | Brunsdon, Fotheringham & Charlton |
| Tipo≠ | Spatially varying regression model | Spatially varying coefficient regression |
| Fonte seminal≠ | LeSage, J. P., & Pace, R. K. (2009). Introduction to Spatial Econometrics. CRC Press / Taylor & Francis. ISBN: 978-1420064247 | Fotheringham, A. S., Brunsdon, C., & Charlton, M. (2002). Geographically Weighted Regression: The Analysis of Spatially Varying Relationships. Wiley. ISBN: 978-0471496168 |
| Outros nomes | local SDM, geographically weighted Spatial Durbin Model, GW-SDM, spatially varying Durbin model | locally weighted spatial regression, spatially varying coefficient model, local spatial model, place-based regression |
| Relacionados≠ | 5 | 6 |
| Resumo≠ | The Local Spatial Durbin Model (Local SDM) extends the global Spatial Durbin Model by allowing regression coefficients to vary across geographic space. It combines the SDM's ability to capture both spatial lag of the dependent variable and spatial lags of covariates with a geographically weighted estimation framework, producing location-specific direct and indirect spillover effects. | Local Spatial Regression fits a separate regression model at each location in a study area, allowing regression coefficients to vary continuously across space. Rather than forcing one global slope on all observations, it reveals where and how the relationship between predictors and an outcome changes geographically — producing a map of coefficients rather than a single number. |
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