مقایسهٔ روشها
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| مدل خودهمبستگی فضایی-زمانی وابسته× | خودهمبستگی فضایی× | |
|---|---|---|
| حوزه | تحلیل فضایی | تحلیل فضایی |
| خانواده | Regression model | Regression model |
| سال پیدایش≠ | 2003-2008 | 1950 |
| پدیدآور≠ | Anselin, Le Gallo & Jayet; Elhorst | P. A. P. Moran (global measure, 1950); Roy Geary (Geary's C, 1954); Luc Anselin (LISA, 1995) |
| نوع≠ | Spatial panel regression | Spatial statistic / exploratory spatial data analysis |
| منبع بنیادین≠ | 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 ↗ |
| نامهای دیگر | ST-SAR, spatial-temporal lag model, spatiotemporal autoregressive model, space-time SAR model | spatial dependence, geographic autocorrelation, spatial clustering measure, SA |
| مرتبط | 5 | 5 |
| خلاصه≠ | 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. |
| ScholarGateمجموعهداده ↗ |
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