Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Lokālā telpiskā regresija× | Ģeogrāfiski svērtā regresija (GWR)× | |
|---|---|---|
| Nozare | Telpiskā analīze | Telpiskā analīze |
| Saime | Regression model | Regression model |
| Izcelsmes gads≠ | 1996 | 2002 |
| Autors≠ | Brunsdon, Fotheringham & Charlton | Fotheringham, Brunsdon & Charlton |
| Tips≠ | Spatially varying coefficient regression | Local spatial regression |
| Pirmavots | Fotheringham, A. S., Brunsdon, C., & Charlton, M. (2002). Geographically Weighted Regression: The Analysis of Spatially Varying Relationships. Wiley. ISBN: 978-0471496168 | Fotheringham, A. S., Brunsdon, C., & Charlton, M. (2002). Geographically Weighted Regression: The Analysis of Spatially Varying Relationships. Wiley. ISBN: 978-0471496168 |
| Citi nosaukumi | locally weighted spatial regression, spatially varying coefficient model, local spatial model, place-based regression | GWR, local regression, spatially varying coefficient regression, Coğrafi Ağırlıklı Regresyon (GWR) |
| Saistītās≠ | 6 | 5 |
| Kopsavilkums≠ | Local Spatial Regression fits a separate regression model at each location in a study area, allowing regression coefficients to vary continuously across space. Rather than forcing one global slope on all observations, it reveals where and how the relationship between predictors and an outcome changes geographically — producing a map of coefficients rather than a single number. | 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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