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Robust Universal Kriging×Regressió Ponderada Geogràficament (GWR)×
CampAnàlisi espacialAnàlisi espacial
FamíliaRegression modelRegression model
Any d'origen1980s–1990s2002
Autor originalDeveloped through contributions of Cressie, Genton, and Rousseeuw in geostatistics and robust statisticsFotheringham, Brunsdon & Charlton
TipusSpatial interpolation modelLocal spatial regression
Font seminalCressie, N. A. C. (1993). Statistics for Spatial Data (revised ed.). Wiley-Interscience, New York. ISBN: 978-0471002550Fotheringham, A. S., Brunsdon, C., & Charlton, M. (2002). Geographically Weighted Regression: The Analysis of Spatially Varying Relationships. Wiley. ISBN: 978-0471496168
ÀliesRUK, robust kriging with external drift, outlier-resistant universal kriging, robust geostatistical regression krigingGWR, local regression, spatially varying coefficient regression, Coğrafi Ağırlıklı Regresyon (GWR)
Relacionats45
ResumRobust 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.
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ScholarGateCompara mètodes: Robust Universal Kriging · Geographically Weighted Regression. Recuperat el 2026-06-18 de https://scholargate.app/ca/compare