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الانحدار الموزون جغرافيًا (GWR)×نموذج التباطؤ المكاني (SAR / الانحدار الذاتي المكاني)×
المجالالتحليل المكانيالتحليل المكاني
العائلةRegression modelRegression model
سنة النشأة20021988
صاحب الطريقةFotheringham, Brunsdon & CharltonAnselin (textbook formalisation); LeSage & Pace
النوعLocal spatial regressionSpatial autoregressive regression
المصدر التأسيسيFotheringham, 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 ↗
الأسماء البديلةGWR, local regression, spatially varying coefficient regression, Coğrafi Ağırlıklı Regresyon (GWR)SAR model, spatial autoregressive model, spatial lag, Uzamsal Gecikme Modeli (SAR / Spatial Lag)
ذات صلة55
الملخصGeographically 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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ScholarGateقارن الطرق: Geographically Weighted Regression · Spatial Lag Model. استُرجع بتاريخ 2026-06-18 من https://scholargate.app/ar/compare