方法对比
并排查看您选择的方法；存在差异的行会高亮显示。
| 时空空间滞后模型× | 空间自相关× | |
|---|---|---|
| 领域 | 空间分析 | 空间分析 |
| 方法族 | Regression model | Regression model |
| 起源年份≠ | 2003-2008 | 1950 |
| 提出者≠ | Anselin, Le Gallo & Jayet; Elhorst | P. A. P. Moran (global measure, 1950); Roy Geary (Geary's C, 1954); Luc Anselin (LISA, 1995) |
| 类型≠ | Spatial panel regression | Spatial statistic / exploratory spatial data analysis |
| 开创性文献≠ | Anselin, L., Le Gallo, J., & Jayet, H. (2008). Spatial Panel Econometrics. In L. Matyas & P. Sevestre (Eds.), The Econometrics of Panel Data (pp. 625-660). Springer. link ↗ | Moran, P. A. P. (1950). Notes on continuous stochastic phenomena. Biometrika, 37(1/2), 17–23. DOI ↗ |
| 别名 | ST-SAR, spatial-temporal lag model, spatiotemporal autoregressive model, space-time SAR model | spatial dependence, geographic autocorrelation, spatial clustering measure, SA |
| 相关 | 5 | 5 |
| 摘要≠ | The Space-Time Spatial Lag Model extends the classic spatial autoregressive (SAR) lag model to panel data, capturing how the outcome in each location at each time point is influenced by the contemporaneous outcomes of neighboring locations, while also controlling for unit-specific and time-specific fixed effects. | Spatial autocorrelation quantifies the degree to which a variable's values at nearby locations resemble each other more (positive autocorrelation) or less (negative autocorrelation) than expected by chance. Global indices such as Moran's I summarise the pattern across the entire study area, while local variants reveal clusters and outliers at the level of individual observations. |
| ScholarGate数据集 ↗ |
|
|