Comparar métodos
Examine os métodos selecionados lado a lado; as linhas que diferem ficam destacadas.
| Robust Universal Kriging× | Regressão Geograficamente Ponderada (GWR)× | |
|---|---|---|
| Área | Análise espacial | Análise espacial |
| Família | Regression model | Regression model |
| Ano de origem≠ | 1980s–1990s | 2002 |
| Autor original≠ | Developed through contributions of Cressie, Genton, and Rousseeuw in geostatistics and robust statistics | Fotheringham, Brunsdon & Charlton |
| Tipo≠ | Spatial interpolation model | Local spatial regression |
| Fonte seminal≠ | Cressie, N. A. C. (1993). Statistics for Spatial Data (revised ed.). Wiley-Interscience, New York. ISBN: 978-0471002550 | Fotheringham, A. S., Brunsdon, C., & Charlton, M. (2002). Geographically Weighted Regression: The Analysis of Spatially Varying Relationships. Wiley. ISBN: 978-0471496168 |
| Outros nomes | RUK, robust kriging with external drift, outlier-resistant universal kriging, robust geostatistical regression kriging | GWR, local regression, spatially varying coefficient regression, Coğrafi Ağırlıklı Regresyon (GWR) |
| Relacionados≠ | 4 | 5 |
| Resumo≠ | Robust Universal Kriging (RUK) is a geostatistical interpolation method that combines a spatially varying deterministic trend with a stochastic residual surface, while using robust estimators to protect the variogram and trend coefficients from the distorting influence of outlying 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. |
| ScholarGateConjunto de dados ↗ |
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