方法对比
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| 时空空间回归× | 空间杜宾模型 (SDM)× | |
|---|---|---|
| 领域 | 空间分析 | 空间分析 |
| 方法族 | Regression model | Regression model |
| 起源年份≠ | 1990s–2000s | 2009 |
| 提出者≠ | Anselin, LeSage, Pace and colleagues in spatial econometrics | LeSage & Pace |
| 类型≠ | Spatio-temporal regression model | Spatial regression model |
| 开创性文献≠ | LeSage, J. P., & Pace, R. K. (2009). Introduction to Spatial Econometrics. CRC Press / Taylor & Francis. ISBN: 978-1420064247 | LeSage, J. & Pace, R. K. (2009). Introduction to Spatial Econometrics. CRC Press. DOI ↗ |
| 别名≠ | spatio-temporal regression, spatial panel regression, space-time regression, ST spatial regression | SDM, spatial mixed model, uzamsal durbin modeli |
| 相关≠ | 6 | 5 |
| 摘要≠ | Space-Time Spatial Regression extends classical spatial regression to panel settings where georeferenced units are observed across multiple time periods. By embedding a spatial weights matrix into a panel regression framework, it simultaneously controls for spatial dependence among cross-sectional units and temporal dynamics, yielding unbiased and consistent estimates in spatio-temporal data. | The Spatial Durbin Model is a general spatial regression model that includes a spatial lag of both the dependent variable (ρWy) and the explanatory variables (WXθ). Introduced as the recommended starting point by LeSage and Pace (2009), it nests the spatial autoregressive (SAR) and spatial error (SEM) models as special cases. |
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