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Regresi Berbobot Geografis (GWR)×Universal Kriging (Kriging dengan Tren)×
BidangAnalisis SpasialAnalisis Spasial
KeluargaRegression modelRegression model
Tahun asal20021969
PencetusFotheringham, Brunsdon & CharltonGeorges Matheron
TipeLocal spatial regressionGeostatistical interpolation with spatial trend
Sumber perintisFotheringham, A. S., Brunsdon, C., & Charlton, M. (2002). Geographically Weighted Regression: The Analysis of Spatially Varying Relationships. Wiley. ISBN: 978-0471496168Matheron, G. (1963). Principles of geostatistics. Economic Geology, 58(8), 1246–1266. DOI ↗
AliasGWR, local regression, spatially varying coefficient regression, Coğrafi Ağırlıklı Regresyon (GWR)kriging with a trend, kriging with drift, trend kriging, evrensel kriging
Terkait53
RingkasanGeographically 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.Universal kriging generalizes ordinary kriging to data whose mean varies systematically across space — a spatial trend or 'drift'. It models the mean as a function of the coordinates (or covariates) and krigs the residuals, so it can interpolate variables that drift in a preferred direction, such as temperature falling with latitude or a pollutant gradient, while still returning prediction variances.
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ScholarGateBandingkan metode: Geographically Weighted Regression · Universal Kriging. Diakses 2026-06-20 dari https://scholargate.app/id/compare