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地理的に重み付けされた回帰分析 (GWR)×ユニバーサル・クリーギング(トレンド付きクリーギング)×
分野空間分析空間分析
系統Regression modelRegression model
提唱年20021969
提唱者Fotheringham, Brunsdon & CharltonGeorges Matheron
種類Local spatial regressionGeostatistical interpolation with spatial trend
原典Fotheringham, 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 ↗
別名GWR, local regression, spatially varying coefficient regression, Coğrafi Ağırlıklı Regresyon (GWR)kriging with a trend, kriging with drift, trend kriging, evrensel kriging
関連53
概要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.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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ScholarGate手法を比較: Geographically Weighted Regression · Universal Kriging. 2026-06-20に以下より取得 https://scholargate.app/ja/compare