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| Hồi quy Trọng số Địa lý Cục bộ (GWR)× | Tự tương quan không gian cục bộ× | |
|---|---|---|
| Lĩnh vực | Phân tích không gian | Phân tích không gian |
| Họ | Regression model | Regression model |
| Năm ra đời≠ | 1996 | 1995 |
| Người khởi xướng≠ | Brunsdon, Fotheringham & Charlton | Luc Anselin |
| Loại≠ | Spatially varying coefficient regression | Spatial association analysis |
| Công trình gốc≠ | Fotheringham, A. S., Brunsdon, C., & Charlton, M. (2002). Geographically Weighted Regression: The Analysis of Spatially Varying Relationships. Wiley. ISBN: 978-0471496168 | Anselin, L. (1995). Local indicators of spatial association — LISA. Geographical Analysis, 27(2), 93–115. DOI ↗ |
| Tên gọi khác | GWR, geographically weighted regression, local spatial regression, spatially varying coefficient model | local spatial association, local SA, LISA methods, local spatial clustering |
| Liên quan≠ | 5 | 6 |
| Tóm tắt≠ | Local Geographically Weighted Regression (GWR) estimates a separate regression model at each location in the study area, allowing every coefficient to vary spatially. By weighting nearby observations more heavily than distant ones, GWR reveals how predictor-outcome relationships shift across geographic space rather than forcing a single global estimate on heterogeneous data. | Local Spatial Autocorrelation methods decompose global spatial clustering into location-specific statistics, revealing where in a study area significant clustering or dispersion occurs. Each observation receives its own association score and significance value, enabling the detection of spatial hot spots, cold spots, and spatial outliers rather than reporting a single summary statistic. |
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