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。
| 局部网络空间分析× | 地理加权回归 (GWR)× | |
|---|---|---|
| 领域 | 空间分析 | 空间分析 |
| 方法族 | Regression model | Regression model |
| 起源年份≠ | 1990s–2000s | 2002 |
| 提出者≠ | Okabe, Sugihara, and spatial network analysis community | Fotheringham, Brunsdon & Charlton |
| 类型≠ | Spatial network analysis | Local spatial regression |
| 开创性文献≠ | Okabe, A., & Sugihara, K. (2012). Spatial Analysis Along Networks: Statistical and Computational Methods. Wiley. ISBN: 978-0470770818 | Fotheringham, A. S., Brunsdon, C., & Charlton, M. (2002). Geographically Weighted Regression: The Analysis of Spatially Varying Relationships. Wiley. ISBN: 978-0471496168 |
| 别名 | local network analysis, local spatial network analysis, neighborhood network analysis, local graph-based spatial analysis | GWR, local regression, spatially varying coefficient regression, Coğrafi Ağırlıklı Regresyon (GWR) |
| 相关 | 5 | 5 |
| 摘要≠ | Local Network-Based Spatial Analysis computes spatial statistics and network measures — such as accessibility, centrality, and density — within restricted local neighborhoods of a spatial network, revealing how connectivity and flow vary across fine geographic scales rather than globally across the entire network. | 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. |
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