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。
| 地理加权回归 (GWR)× | 空间滞后模型（SAR / 空间自回归）× | |
|---|---|---|
| 领域 | 空间分析 | 空间分析 |
| 方法族 | Regression model | Regression model |
| 起源年份≠ | 2002 | 1988 |
| 提出者≠ | Fotheringham, Brunsdon & Charlton | Anselin (textbook formalisation); LeSage & Pace |
| 类型≠ | Local spatial regression | Spatial autoregressive regression |
| 开创性文献≠ | Fotheringham, A. S., Brunsdon, C., & Charlton, M. (2002). Geographically Weighted Regression: The Analysis of Spatially Varying Relationships. Wiley. ISBN: 978-0471496168 | Anselin, L. (1988). Spatial Econometrics: Methods and Models. Kluwer Academic. DOI ↗ |
| 别名 | GWR, local regression, spatially varying coefficient regression, Coğrafi Ağırlıklı Regresyon (GWR) | SAR model, spatial autoregressive model, spatial lag, Uzamsal Gecikme Modeli (SAR / Spatial Lag) |
| 相关 | 5 | 5 |
| 摘要≠ | Geographically Weighted Regression is a local regression method, introduced by Fotheringham, Brunsdon and Charlton (2002), that allows the regression coefficients to vary across space. Instead of one global equation, it fits a separate set of coefficients at every location, capturing spatial heterogeneity in the relationships. | The Spatial Lag Model is an autoregressive regression that assumes spatial dependence in the dependent variable itself: the outcome values of neighbouring units enter the model as an explanatory term (ρWy). It was formalised in Anselin's Spatial Econometrics (1988) and developed further by LeSage and Pace (2009), and it decomposes spillover effects into direct, indirect, and total impacts. |
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