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地理的に重み付けされた回帰分析 (GWR)×空間ラグモデル(SAR / 空間自己回帰)×
分野空間分析空間分析
系統Regression modelRegression model
提唱年20021988
提唱者Fotheringham, Brunsdon & CharltonAnselin (textbook formalisation); LeSage & Pace
種類Local spatial regressionSpatial autoregressive regression
原典Fotheringham, A. S., Brunsdon, C., & Charlton, M. (2002). Geographically Weighted Regression: The Analysis of Spatially Varying Relationships. Wiley. ISBN: 978-0471496168Anselin, L. (1988). Spatial Econometrics: Methods and Models. Kluwer Academic. DOI ↗
別名GWR, local regression, spatially varying coefficient regression, Coğrafi Ağırlıklı Regresyon (GWR)SAR model, spatial autoregressive model, spatial lag, Uzamsal Gecikme Modeli (SAR / Spatial Lag)
関連55
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.The Spatial Lag Model is an autoregressive regression that assumes spatial dependence in the dependent variable itself: the outcome values of neighbouring units enter the model as an explanatory term (ρWy). It was formalised in Anselin's Spatial Econometrics (1988) and developed further by LeSage and Pace (2009), and it decomposes spillover effects into direct, indirect, and total impacts.
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ScholarGate手法を比較: Geographically Weighted Regression · Spatial Lag Model. 2026-06-18に以下より取得 https://scholargate.app/ja/compare