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Lokalne Krigowanie Ordinaryjne×Regresja geograficznie ważona (GWR)×
DziedzinaAnaliza przestrzennaAnaliza przestrzenna
RodzinaRegression modelRegression model
Rok powstania1970s–1990s2002
TwórcaJournel & Huijbregts; developed further by Goovaerts and Chiles & DelfinerFotheringham, Brunsdon & Charlton
TypGeostatistical interpolation (local/moving-window variant)Local spatial regression
Źródło pierwotneChiles, J.-P., & Delfiner, P. (1999). Geostatistics: Modeling Spatial Uncertainty. Wiley. ISBN: 978-0471083153Fotheringham, A. S., Brunsdon, C., & Charlton, M. (2002). Geographically Weighted Regression: The Analysis of Spatially Varying Relationships. Wiley. ISBN: 978-0471496168
Inne nazwymoving window kriging, local kriging, neighborhood kriging, LOKGWR, local regression, spatially varying coefficient regression, Coğrafi Ağırlıklı Regresyon (GWR)
Pokrewne55
PodsumowanieLocal Ordinary Kriging (LOK) is a geostatistical interpolation method that estimates values at unsampled locations using only a spatially defined moving neighborhood of nearby observations. By restricting each prediction to a local data window rather than the full dataset, LOK accommodates spatial non-stationarity, reduces computational cost, and often yields more accurate local predictions than global ordinary kriging.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.
ScholarGateZbiór danych
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  2. 2 Źródła
  3. PUBLISHED
  1. v1
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  3. PUBLISHED

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ScholarGatePorównaj metody: Local Ordinary Kriging · Geographically Weighted Regression. Pobrano 2026-06-19 z https://scholargate.app/pl/compare