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Географски претеглена регресия (GWR)×Пространствен лаг модел (SAR / Spatial Autoregressive)×
ОбластПространствен анализПространствен анализ
СемействоRegression modelRegression model
Година на възникване20021988
СъздателFotheringham, Brunsdon & CharltonAnselin (textbook formalisation); LeSage & Pace
ТипLocal spatial regressionSpatial autoregressive regression
Основополагащ източникFotheringham, 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 ↗
Други названияGWR, local regression, spatially varying coefficient regression, Coğrafi Ağırlıklı Regresyon (GWR)SAR model, spatial autoregressive model, spatial lag, Uzamsal Gecikme Modeli (SAR / Spatial Lag)
Свързани55
РезюмеGeographically 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.
ScholarGateНабор от данни
  1. v1
  2. 1 Източници
  3. PUBLISHED
  1. v1
  2. 2 Източници
  3. PUBLISHED

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ScholarGateСравнение на методи: Geographically Weighted Regression · Spatial Lag Model. Извлечено на 2026-06-18 от https://scholargate.app/bg/compare