مقایسهٔ روشها
روشهای انتخابی خود را کنار هم مرور کنید؛ ردیفهای متفاوت برجسته شدهاند.
| خودهمبستگی فضایی× | رگرسیون وزنی جغرافیایی (GWR)× | |
|---|---|---|
| حوزه | تحلیل فضایی | تحلیل فضایی |
| خانواده | Regression model | Regression model |
| سال پیدایش≠ | 1950 | 2002 |
| پدیدآور≠ | P. A. P. Moran (global measure, 1950); Roy Geary (Geary's C, 1954); Luc Anselin (LISA, 1995) | Fotheringham, Brunsdon & Charlton |
| نوع≠ | Spatial statistic / exploratory spatial data analysis | Local spatial regression |
| منبع بنیادین≠ | Moran, P. A. P. (1950). Notes on continuous stochastic phenomena. Biometrika, 37(1/2), 17–23. DOI ↗ | Fotheringham, A. S., Brunsdon, C., & Charlton, M. (2002). Geographically Weighted Regression: The Analysis of Spatially Varying Relationships. Wiley. ISBN: 978-0471496168 |
| نامهای دیگر | spatial dependence, geographic autocorrelation, spatial clustering measure, SA | GWR, local regression, spatially varying coefficient regression, Coğrafi Ağırlıklı Regresyon (GWR) |
| مرتبط | 5 | 5 |
| خلاصه≠ | 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. | 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. |
| ScholarGateمجموعهداده ↗ |
|
|