方法对比
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| 面板普通克里金× | 面板空间回归× | |
|---|---|---|
| 领域 | 空间分析 | 空间分析 |
| 方法族 | Regression model | Regression model |
| 起源年份≠ | 1963 (Ordinary Kriging origin); panel extensions formalized in 1990s–2000s | 1988-2014 |
| 提出者≠ | Extension of Ordinary Kriging (Matheron, 1963) to panel/longitudinal spatial settings | Anselin, Elhorst, and colleagues in spatial econometrics |
| 类型≠ | Geostatistical spatial interpolation | Spatial panel regression |
| 开创性文献≠ | Cressie, N. A. C. (1993). Statistics for Spatial Data (revised ed.). Wiley-Interscience. ISBN: 978-0471002550 | Elhorst, J. P. (2014). Spatial Econometrics: From Cross-Sectional Data to Spatial Panels. Springer. ISBN: 978-3642403408 |
| 别名 | ordinary kriging for panel data, longitudinal ordinary kriging, repeated-measures spatial kriging, panel geostatistical interpolation | spatial panel model, panel spatial econometrics, spatial panel data regression, PSR |
| 相关 | 6 | 6 |
| 摘要≠ | Panel Ordinary Kriging extends the classical geostatistical interpolation method — Ordinary Kriging — to panel (longitudinal) datasets where the same set of spatial locations is observed repeatedly over multiple time periods. It produces optimal linear unbiased predictions at unsampled locations for each time slice, accounting for spatial dependence while leveraging the temporal structure of the repeated observations. | Panel Spatial Regression extends standard panel data models by explicitly accounting for spatial dependence among cross-sectional units observed over time. It combines the temporal control of panel fixed or random effects with a spatial weights matrix that encodes geographic or network proximity, yielding unbiased and efficient estimates when observations are spatially correlated across units. |
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